Sleuth2 Manual

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Package ‘Sleuth2’
January 24, 2019
Title Data Sets from Ramsey and Schafer's ``Statistical Sleuth (2nd Ed)''
Version 2.0-5
Date 2019-01-24
Author Original by F.L. Ramsey and D.W. Schafer;
modifications by Daniel W. Schafer, Jeannie Sifneos and Berwin
A. Turlach; vignettes contributed by Nicholas Horton, Kate Aloisio
and Ruobing Zhang, with corrections by Randall Pruim
Description Data sets from Ramsey, F.L. and Schafer, D.W. (2002), ``The
Statistical Sleuth: A Course in Methods of Data Analysis (2nd
ed)'', Duxbury.
Maintainer Berwin A Turlach <Berwin.Turlach@gmail.com>
LazyData yes
Depends R (>= 3.5.0)
Suggests lattice, knitr, MASS, agricolae, car, gmodels, leaps, mosaic
VignetteBuilder knitr
License GPL (>= 2)
URL http://r-forge.r-project.org/projects/sleuth2/
Rtopics documented:
Sleuth2-package....................................... 4
case0101 .......................................... 5
case0102 .......................................... 5
case0201 .......................................... 6
case0202 .......................................... 7
case0301 .......................................... 8
case0302 .......................................... 9
case0401 .......................................... 9
case0402 .......................................... 10
case0501 .......................................... 11
case0502 .......................................... 12
case0601 .......................................... 13
case0602 .......................................... 14
case0701 .......................................... 15
case0702 .......................................... 16
case0801 .......................................... 17
1
2Rtopics documented:
case0802 .......................................... 17
case0901 .......................................... 18
case0902 .......................................... 19
case1001 .......................................... 19
case1002 .......................................... 20
case1101 .......................................... 21
case1102 .......................................... 22
case1201 .......................................... 23
case1202 .......................................... 24
case1301 .......................................... 25
case1302 .......................................... 26
case1401 .......................................... 27
case1402 .......................................... 28
case1501 .......................................... 29
case1502 .......................................... 30
case1601 .......................................... 31
case1602 .......................................... 32
case1701 .......................................... 33
case1702 .......................................... 34
case1902 .......................................... 35
case2001 .......................................... 37
case2002 .......................................... 38
case2101 .......................................... 39
case2102 .......................................... 40
case2201 .......................................... 41
case2202 .......................................... 41
ex0112............................................ 42
ex0116............................................ 43
ex0211............................................ 44
ex0221............................................ 44
ex0222............................................ 45
ex0223............................................ 46
ex0321............................................ 46
ex0323............................................ 47
ex0327............................................ 48
ex0328............................................ 49
ex0331............................................ 49
ex0332............................................ 50
ex0333............................................ 51
ex0428............................................ 51
ex0429............................................ 52
ex0430............................................ 53
ex0431............................................ 53
ex0432............................................ 54
ex0518............................................ 55
ex0523............................................ 55
ex0524............................................ 56
ex0621............................................ 57
ex0622............................................ 57
ex0723............................................ 59
ex0724............................................ 60
ex0726............................................ 61
Rtopics documented: 3
ex0727............................................ 61
ex0728............................................ 62
ex0729............................................ 63
ex0730............................................ 63
ex0816............................................ 64
ex0817............................................ 65
ex0818............................................ 66
ex0820............................................ 66
ex0822............................................ 67
ex0823............................................ 68
ex0824............................................ 69
ex0825............................................ 69
ex0914............................................ 70
ex0915............................................ 71
ex0918............................................ 71
ex0920............................................ 72
ex1014............................................ 73
ex1026............................................ 74
ex1027............................................ 74
ex1028............................................ 75
ex1029............................................ 76
ex1115............................................ 77
ex1120............................................ 77
ex1122............................................ 78
ex1123............................................ 79
ex1124............................................ 80
ex1217............................................ 80
ex1220............................................ 82
ex1221............................................ 83
ex1222............................................ 84
ex1317............................................ 85
ex1319............................................ 85
ex1320............................................ 86
ex1414............................................ 87
ex1415............................................ 88
ex1417............................................ 89
ex1509............................................ 89
ex1512............................................ 90
ex1513............................................ 91
ex1514............................................ 91
ex1515............................................ 92
ex1605............................................ 93
ex1611............................................ 94
ex1612............................................ 94
ex1613............................................ 95
ex1614............................................ 96
ex1615............................................ 96
ex1708............................................ 97
ex1713............................................ 98
ex1714............................................ 99
ex1914............................................100
ex1916............................................100
4Sleuth2-package
ex1917............................................101
ex1918............................................102
ex1919............................................103
ex2011............................................103
ex2012............................................104
ex2015............................................105
ex2016............................................106
ex2017............................................107
ex2018............................................108
ex2115............................................109
ex2116............................................110
ex2117............................................111
ex2118............................................112
ex2119............................................113
ex22.20 ...........................................114
ex2216............................................114
ex2222............................................115
ex2223............................................116
ex2224............................................117
ex2225............................................118
ex2414............................................118
Sleuth2Manual .......................................119
Index 120
Sleuth2-package The R Sleuth2 package
Description
Data sets from Ramsey and Schafer’s "Statistical Sleuth (2nd ed)"
Details
This package contains a variety of datasets. For a complete list, use library(help="Sleuth2") or
Sleuth2Manual().
Author(s)
Original by F.L. Ramsey and D.W. Schafer
Modifications by Daniel W Schafer, Jeannie Sifneos and Berwin A Turlach
Maintainer: Berwin A Turlach <Berwin.Turlach@gmail.com>
case0101 5
case0101 Motivation and Creativity
Description
Data from an experiment concerning the effects of intrinsic and extrinsic motivation on creativity.
Subjects with considerable experience in creative writing were randomly assigned to one of two
treatment groups.
Usage
case0101
Format
A data frame with 47 observations on the following 2 variables.
Score creativity score
Treatment factor denoting the treatment group
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Amabile, T. (1985). Motivation and Creativity: Effects of Motivational Orientation on Creative
Writers, Journal of Personality and Social Psychology 48(2): 393–399.
Examples
str(case0101)
boxplot(Score~Treatment, case0101)
case0102 Sex Discrimination in Employment
Description
The data are the beginning salaries for all 32 male and all 61 female skilled, entry–level clerical
employees hired by a bank between 1969 and 1977.
Usage
case0102
6case0201
Format
A data frame with 93 observations on the following 2 variables.
Salary starting salaries (in US$)
Sex sex of the clerical employee
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Roberts, H.V. (1979). Harris Trust and Savings Bank: An Analysis of Employee Compensation,
Report 7946, Center for Mathematical Studies in Business and Economics, University of Chicago
Graduate School of Business.
See Also
case1202
Examples
str(case0102)
boxplot(Salary~Sex, case0102)
case0201 Bumpus’s Data on Natural Selection (Humerus)
Description
As evidence in support of natural selection, Bumpus presented measurements on house sparrows
brought to the Anatomical Laboratory of Brown University after an uncommonly severe winter
storm. Some of these birds had survived and some had perished. Bumpus asked whether those that
perished did so because they lacked physical characteristics enabling them to withstand the intensity
of that particular instance of selective elimination. The data are on the humerus (arm bone) lengths
for the 24 adult male sparrows that perished and for the 35 adult males that survived.
Usage
case0201
Format
A data frame with 59 observations on the following 2 variables.
Humerus Humerus length of adult male sparrows (in inches)
Status factor variable indicating whether the sparrow perished or survived in a winter storm
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
case0202 7
See Also
ex0221,ex2016
Examples
str(case0201)
with(subset(case0201, Status=="Perished"), stem(Humerus, scale=10))
with(subset(case0201, Status=="Survived"), stem(Humerus))
case0202 Anatomical Abnormalities Associated with Schizophrenia
Description
Are any physiological indicators associated with schizophrenia? In a 1990 article, researchers re-
ported the results of a study that controlled for genetic and socioeconomic differences by examining
15 pairs of monozygotic twins, where one of the twins was schizophrenic and the other was not.
The researchers used magnetic resonance imaging to measure the volumes (in cm$^3$) of several
regions and subregions of the twins’ brains.
Usage
case0202
Format
A data frame with 15 observations on the following 2 variables.
Unaffect volume of left hippocampus of unaffected twin (in cm3)
Affected volume of left hippocampus of affected twin (in cm3)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Suddath, R.L., Christison, G.W., Torrey, E.F., Casanova, M.F. and Weinberger, D.R. (1990). Anatom-
ical Abnormalities in the Brains of Monozygotic Twins Discordant for Schizophrenia, New England
Journal of Medicine 322(12): 789–794.
Examples
str(case0202)
with(case0202, stem(Unaffect-Affected, scale=2))
8case0301
case0301 Cloud Seeding
Description
Does dropping silver iodide onto clouds increase the amount of rainfall they produce? In a random-
ized experiment, researchers measured the volume of rainfall in a target area (in acre-feet) on 26
suitable days in which the clouds were seeded and on 26 suitble days in which the clouds were not
seeded.
Usage
case0301
Format
A data frame with 52 observations on the following 2 variables.
Rainfall the volume of rainfall in the target area (in acre-feet)
Treatment a factor with levels "Unseeded" and "Seeded" indicating whether the clouds were
unseeded or seeded.
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Simpson, J., Olsen, A., and Eden, J. (1975). A Bayesian Analysis of a Multiplicative Treatment
Effect in Weather Modification. Technometrics 17: 161–166.
Examples
str(case0301)
boxplot(Rainfall ~ Treatment, case0301)
boxplot(log(Rainfall) ~ Treatment, case0301)
library(lattice)
bwplot(Treatment ~ log(Rainfall), case0301)
bwplot(log(Rainfall) ~ Treatment, case0301)
case0302 9
case0302 Agent Orange
Description
In 1987, researchers measured the TCDD concentration in blood samples from 646 U.S. veterans of
the Vietnam War and from 97 U.S. veterans who did not serve in Vietnam. TCDD is a carcinogenic
dioxin in the herbicide called Agent Orange, which was used to clear jungle hiding areas by the
U.S. military in the Vietnam War between 1962 and 1970.
Usage
data(case0302)
Format
A data frame with 743 observations on the following 2 variables.
Dioxin the concentration of TCDD, in parts per trillion
Veteran factor variable with two levels, "Vietnam" and "Other", to indicate the type of veteran
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Centers for Disease Control Veterans Health Studies: Serum 2,3,7,8-Tetraclorodibenzo-p-dioxin
Levels in U.S. Army Vietnam-era Veterans. Journal of the American Medical Association 260:
1249–1254.
Examples
str(case0302)
boxplot(Dioxin ~ Veteran, case0302)
t.test(Dioxin ~ Veteran, case0302)
## To examine results with largest dioxin omitted
t.test(Dioxin ~ Veteran, case0302, subset=(Dioxin < 40))
case0401 Space Shuttle
Description
The number of space shuttle O-ring incidents for 4 space shuttle launches when the air temperatures
was below 65 degrees F and for 20 space shuttle launches when the air temperature was above 65
degrees F.
10 case0402
Usage
case0401
Format
A data frame with 24 observations on the following 2 variables.
Incidents the number of O-ring incidents
Launch factor variable with two levels—"Cool" and "Warm"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Feynman, R.P. (1988). What do You Care What Other People Think? W. W. Norton.
See Also
ex2011,ex2223
Examples
str(case0401)
stem(subset(case0401, Launch=="Cool", Incidents, drop=TRUE))
stem(subset(case0401, Launch=="Warm", Incidents, drop=TRUE))
case0402 Cognitive Load
Description
Educational researchers randomly assigned 28 ninth-year students in Australia to receive coordinate
geometry training in one of two ways: a conventional way and a modified way. After the training,
the students were asked to solve a coordinate geometry problem. The time to complete the problem
was recorded, but five students in the “conventional” group did not complete the solution in the five
minute alloted time.
Usage
case0402
Format
A data frame with 28 observations on the following 3 variables.
Time the time (in seconds) that the student worked on the problem
Treatmt factor variable with two levels—"Modified" and "Conventional"
Censor 1 if the individual did not complete the problem in 5 minutes, 0 if they did
case0501 11
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Sweller, J., Chandler, P., Tierney, P. and Cooper, M. (1990). Cognitive Load as a Factor in the
Structuring of Technical Material, Journal of Experimental Psychology General 119(2): 176–192.
Examples
str(case0402)
stem(subset(case0402, Treatmt=="Conventional", Time, drop=TRUE))
stem(subset(case0402, Treatmt=="Modified", Time, drop=TRUE))
wilcox.test(Time ~ Treatmt, case0402)
case0501 Diet Restriction and Longevity
Description
Female mice were randomly assigned to six treatment groups to investigate whether restricting
dietary intake increases life expectancy. Diet treatments were:
1. "NP"—mice ate unlimited amount of nonpurified, standard diet
2. "N/N85"—mice fed normally before and after weaning. After weaning, ration was controlled
at 85 kcal/wk
3. "N/R50"—normal diet before weaning and reduced calorie diet (50 kcal/wk) after weaning
4. "R/R50"—reduced calorie diet of 50 kcal/wk both before and after weaning
5. "N/R50 lopro"—normal diet before weaning, restricted diet (50 kcal/wk) after weaning and
dietary protein content decreased with advancing age
6. "N/R40"—normal diet before weaning and reduced diet (40 Kcal/wk) after weaning.
Usage
case0501
Format
A data frame with 349 observations on the following 2 variables.
Lifetime the lifetime of the mice (in months)
Diet factor variable with six levels—"NP","N/N85","lopro","N/R50","R/R50" and "N/R40"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
12 case0502
References
Weindruch, R., Walford, R.L., Fligiel, S. and Guthrie D. (1986). The Retardation of Aging in
Mice by Dietary Restriction: Longevity, Cancer, Immunity and Lifetime Energy Intake, Journal of
Nutrition 116(4):641–54.
Examples
str(case0501)
boxplot(Lifetime~Diet, width=c(rep(.8,6)), data=case0501,
xlab="Diet", ylab="Lifetime in months")
summary(subset(case0501, Diet=="NP", Lifetime))
case0502 The Spock Conspiracy Trial
Description
In 1968, Dr. Benjamin Spock was tried in Boston on charges of conspiring to violate the Selective
Service Act by encouraging young men to resist being drafted into military service for Vietnam.
The defence in the case challenged the method of jury selection claiming that women were un-
derrepresented. Boston juries are selected in three stages. First 300 names are selected at random
from the City Directory, then a venire of 30 or more jurors is selected from the initial list of 300
and finally, an actual jury is selected from the venire in a nonrandom process allowing each side to
exclude certain jurors. There was one woman on the venire and no women on the final list. The de-
fence argued that the judge in the trial had a history of venires in which women were systematically
underrepresented and compared the judge’s recent venires with the venires of six other Boston area
district judges.
Usage
case0502
Format
A data frame with 46 observations on the following 2 variables.
Percent is the percent of women on the venire’s of the Spock trial judge and 6 other Boston area
judges
Judge a factor with levels "Spock's","A","B","C","D","E" and "F"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Zeisel, H. and Kalven, H. Jr. (1972). Parking Tickets and Missing Women: Statistics and the Law
in Tanur, J.M. et al. (eds.) Statistics: A Guide to the Unknown, Holden-Day.
case0601 13
Examples
str(case0502)
boxplot(Percent~Judge, data=case0502,
xlab="Judge",ylab="Percentage of Women")
percent.spocks <- subset(case0502, Judge == "Spock's", Percent)
percent.others <- subset(case0502, Judge != "Spock's", Percent)
t.test( percent.spocks,percent.others)
summary(aov(Percent~Judge, case0502, subset = Judge != "Spock's"))
#as in Display 5.10
summary(aov(Percent~Judge, case0502))
case0601 Discrimination Against the Handicapped
Description
Study explores how physical handicaps affect people’s perception of employment qualifications.
Researchers prepared 5 videotaped job interviews using actors with a script designed to reflect an
interview with an applicant of average qualifications. The 5 tapes differed only in that the applicant
appeared with a different handicap in each one. Seventy undergraduate students were randomly
assigned to view the tapes and rate the qualification of the applicant on a 0-10 point scale.
Usage
case0601
Format
A data frame with 70 observations on the following 2 variables.
Score is the score each student gave to the applicant
Handicap is a factor variable with 5 levels—"None","Amputee","Crutches","Hearing" and
"Wheelchair"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Cesare, S.J., Tannenbaum, R.J. and Dalessio, A. (1990). Interviewers’ Decisions Related to Appli-
cant Handicap Type and Rater Empathy, Human Performance 3(3): 157–171.
Examples
str(case0601)
boxplot(Score~Handicap, data=case0601, ylab="Score")
aov.handicap <- aov(Score ~ Handicap, case0601)
summary(aov.handicap)
TukeyHSD(aov.handicap)
14 case0602
#Calculate confidence interval for linear combination
#(wheelchair+crutches)/2 - (amputee+hearing)/2 as in Display 6.4
mean.handicaps <- with(case0601, tapply(Score, Handicap, mean))
var.handicaps <- with(case0601, tapply(Score, Handicap, var))
n <- 14
s.pooled <- sqrt(sum((n-1)*var.handicaps)/sum((n-1)*5))
## either
cr.wh <- mean.handicaps["Wheelchair"] + mean.handicaps["Crutches"]
am.he <- mean.handicaps["Amputee"] + mean.handicaps["Hearing"]
g <- cr.wh/2 - am.he/2
## or
contr <- c(0, -1, 1, -1, 1)/2
g <- sum(contr * mean.handicaps)
se.g <- s.pooled * sqrt(sum(contr^2)/n)
t.65 <- qt(.975, 65)
## ci
g + c(-1,1) * t.65 * se.g
case0602 Mate Preference of Platyfish
Description
Do female Platyfish prefer male Platyfish with yellow swordtails? A.L. Basolo proposed and tested
a selection model in which females have a pre-existing bias for a male trait even before the males
possess it. Six pairs of males were surgically given artificial, plastic swordtails—one pair received
a bright yellow sword, the other a transparent sword. Females were given the opportunity to engage
in courtship activity with either of the males. Of the total time spent by each female engaged in
courtship during a 20 minute observation period, the percentages of time spent with the yellow-
sword male were recorded.
Usage
case0602
Format
A data frame with 84 observations on the following 3 variables.
Proportion The proportion of courtship time spent by 84 females with the yellow-sword males
Pair Factor variable with 6 levels—"Pair 1","Pair 2","Pair 3","Pair 4","Pair 5" and
"Pair 6"
Length Body size of the males
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
case0701 15
References
Basolo, A.L. (1990). Female Preference Predates the Evolution of the Sword in Swordtail Fish,
Science 250: 808–810.
Examples
str(case0602)
boxplot(Proportion~Pair, case0602, ylab="Proportion")
#as in Display 6.5
summary(aov(Proportion~Pair, case0602))
n.fish <- with(case0602, tapply(Proportion, Pair, length))
av.fish <- with(case0602, tapply(Proportion, Pair, mean))
sd.fish <- with(case0602, tapply(Proportion, Pair, sd))
male.body.size <- with(case0602, tapply(Length, Pair, unique))
mean.body <- mean(male.body.size)
table.fish <- data.frame(n.fish, round(av.fish*100,2),
round(sd.fish*100,2), male.body.size,
2*(male.body.size-mean.body))
names(table.fish) <- c("n", "average", "sd", "male.body.size", "coefficient")
s.pooled <- with(table.fish, round(sqrt(sum(sd^2*(n-1))/sum(n-1)),2))
g <- with(table.fish, sum(average*coefficient))
se.g <- with(table.fish, round(s.pooled*sqrt(sum(coefficient^2/n)),2))
g/se.g
case0701 The Big Bang
Description
Hubble’s initial data on 24 nebulae outside the Milky Way.
Usage
case0701
Format
A data frame with 24 observations on the following 2 variables.
Velocity recession velocity (in kilometres per second)
Distance distance from earth (in magaparsec)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Hubble, E. (1929). A Relation Between Distance and Radial Velocity Among Extragalactic Nebu-
lae, Proceedings of the National Academy of Science 15: 168–173.
16 case0702
See Also
ex0727
Examples
str(case0701)
plot(case0701)
case0702 Meat Processing and pH
Description
A certain kind of meat processing may begin once the pH in postmortem muscle of a steer carcass
has decreased sufficiently. To estimate the timepoint at which pH has dropped sufficiently, 10 steer
carcasses were assigned to be measured for pH at one of five times after slaughter.
Usage
case0702
Format
A data frame with 10 observations on the following 2 variables.
Time time after slaughter (hours)
pH pH level in postmortem muscle
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Schwenke, J.R. and Milliken, G.A. (1991). On the Calibration Problem Extended to Nonlinear
Models, Biometrics 47(2): 563–574.
See Also
ex0816
Examples
str(case0702)
plot(case0702)
case0801 17
case0801 Island Area and Number of Species
Description
The data are the numbers of reptile and amphibian species and the island areas for seven islands in
the West Indies.
Usage
case0801
Format
A data frame with 7 observations on the following 2 variables.
Area area of island (in square miles)
Species number of reptile and amphibian species on island
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(case0801)
plot(case0801)
case0802 Breakdown Times for Insulating Fluid under different Voltage
Description
In an industrial laboratory, under uniform conditions, batches of electrical insulating fluid were
subjected to constant voltages until the insulating property of the fluids broke down. Seven different
voltage levels were studied and the measured reponses were the times until breakdown.
Usage
case0802
Format
A data frame with 76 observations on the following 3 variables.
Time times until breakdown (in minutes)
Voltage voltage applied (in kV)
Group factor variable (group number)
18 case0901
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(case0802)
plot(log(Time)~Voltage, case0802)
case0901 Effects of Light on Meadowfoam Flowering
Description
Meadowfoam is a small plant found growing in moist meadows of the US Pacific Northwest. Re-
searchers reported the results from one study in a series designed to find out how to elevate mead-
owfoam production to a profitable crop. In a controlled growth chamber, they focused on the effects
of two light–related factors: light intensity and the timeing of the onset of the ligth treatment.
Usage
case0901
Format
A data frame with 24 observations on the following 3 variables.
Flowers average number of flowers per meadowfoam plant
Time time light intensity regiments started
Intens light intensity (in µmol/m2/sec)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(case0901)
plot(Flowers~Intens, case0901, pch= ifelse(Time=="Early", 19, 21))
case0902 19
case0902 Why Do Some Mammals Have Large Brains for Their Size?
Description
The data are the average values of brain weight, body weight, gestation lengths (length of preg-
nancy) and litter size for 96 species of mammals.
Usage
case0902
Format
A data frame with 96 observations on the following 5 variables.
Species species
Brain average brain weight (in grams)
Body average body weight (in kilograms)
Gestation gestation period (in days)
Litter average litter size
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
case0902
Examples
str(case0902)
pairs(log(Brain)~log(Body)+log(Litter)+Gestation, case0902)
case1001 Galileo’s Data on the Motion of Falling Bodies
Description
In 1609 Galileo proved mathematically that the trajectory of a body falling with a horizontal velocity
component is a parabola. His search for an experimental setting in which horizontal motion was
not affected appreciably (to study inertia) let him to construct a certain apparatus. The data comes
from one of his experiments.
Usage
case1001
20 case1002
Format
A data frame with 7 observations on the following 2 variables.
Distance horizontal distances (in punti)
Height initial height (in punti)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(case1001)
plot(Distance ~ Height, case1001)
case1002 The Energy Costs of Echolocation by Bats
Description
The data are on in–flight energy expenditure and body mass from 20 energy studies on three types
of flying vertebrates: echolocating bats, non–echolocating bats and non–echolocating birds.
Usage
case1002
Format
A data frame with 20 observations on the following 4 variables.
Species species
Mass mass (in grams)
Type a factor with 3 levels indicating the type of flying vertebrate
Energy in–flight energy expenditure (in W)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Speakman, J.R. and Racey, P.A. (1991). No cost of Echolocation for Bats in Flight, Nature 350:
421–423.
case1101 21
Examples
str(case1002)
plot(log(Energy)~log(Mass), case1002,
pch = ifelse(Type=="echolocating bats", 19,
ifelse(Type=="non-echolocating birds", 21, 24)))
plot(Energy~Mass, case1002, log="xy",
xlab = "Body Mass (g) (log scale)",
ylab = "Energy Expenditure (W) (log scale)",
pch = ifelse(Type=="echolocating bats", 19,
ifelse(Type=="non-echolocating birds", 21, 24)))
legend(7, 50, pch=c(24, 21, 19),
c("Non-echolocating bats", "Non-echolocating birds","Echolocating bats"))
library(lattice)
yticks <- c(1,2,5,10,20,50)
xticks <- c(10,20,50,100,200,500)
xyplot(Energy ~ Mass, case1002, groups=Type,
scales = list(log=TRUE, y=list(at=yticks), x=list(at=xticks)),
ylab = "Energy Expenditure (W) (log scale)",
xlab = "Body Mass (g) (log scale)",
auto.key = list(x = 0.2, y = 0.9, corner = c(0, 1), border = TRUE))
case1101 Alcohol Metabolism in Men and Women
Description
These data were collected on 18 women and 14 men to investigate a certain theory on why women
exhibit a lower tolerance for alcohol and develop alcohol–related liver disease more readily than
men.
Usage
case1101
Format
A data frame with 32 observations on the following 5 variables.
Subject subject number in the study
Metabol first–pass metabolism of alcohol in the stomach (in mmol/liter-hour)
Gastric gastric alcohol dehydrogenase activity in the stomach (in µmol/min/g of tissue)
Sex sex of the subject
Alcohol whether the subject is alcoholic or not
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
22 case1102
Examples
str(case1101)
plot(Metabol~Gastric, case1101,
pch=ifelse(Sex=="Female", 19, 21),
col=ifelse(Alcohol=="Alcoholic", "red", "green"))
legend(1,12, pch=c(19,21,19,21), col=c("green","green", "red", "red"),
c("Non-alcoholic Females", "Non-alcoholic Males",
"Alcoholic Females", "Alcoholic Males"))
library(lattice)
xyplot(Metabol~Gastric|Sex*Alcohol, case1101)
xyplot(Metabol~Gastric, case1101, groups=Sex:Alcohol,
auto.key=list(x=0.2, y=0.8, corner=c(0,0), border=TRUE))
case1102 The Blood–Brain Barrier
Description
The human brain is protected from bacteria and toxins, which course through the blood–stream, by
a single layer of cells called the blood–brain barrier. These data come from an experiment (on rats,
which process a similar barrier) to study a method of disrupting the barrier by infusing a solution of
concentrated sugars.
Usage
case1102
Format
A data frame with 34 observations on the following 9 variables.
Brain Brain tumor count (per gm)
Liver Liver count (per gm)
Time Sacrifice time (in hours)
Treat Treatment received
Days Days post inoculation
Sex Sex of the rat
Weight Initial weight (in grams)
Loss Weight loss (in grams)
Tumor Tumor weight (in 10−4grams)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
case1201 23
Examples
str(case1102)
plot(Brain/Liver ~ Time, case1102, log="xy", pch=ifelse(Treat=="BD", 19,21))
legend(10,0.1, pch=c(19,21), c("Saline control", "Barrier disruption"))
case1201 State Average SAT Scores
Description
Data on the average SAT scores for US states in 1982 and possible associated factors.
Usage
case1201
Format
A data frame with 50 observations on the following 8 variables.
State US state
SAT state averages of the total SAT (verbal + quantitative) scores
Takers the percentage of the total eligible students (high school seniors) in the state who took the
exam
Income the median income of families of test–takers (in hundreds of dollars)
Years the average number of years that the test–takers had formal studies in social sciences, natural
sciences and humanities
Public the percentage of the test–takers who attended public secondary schools
Expend the total state expenditure on secondary schools (in hundreds of dollars per student)
Rank the median percentile ranking of the test–takers within their secondary school classes
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(case1201)
pairs(SAT~Rank+Years+Income+Public+Expend, case1201)
24 case1202
case1202 Sex discrimination in Employment
Description
Data on employees from one job category (skilled, entry–level clerical) of a bank that was sued for
sex discrimination. The data are on 32 male and 61 female employees, hired between 1965 and
1975.
Usage
case1202
Format
A data frame with 93 observations on the following 7 variables.
Bsal Annual salary at time of hire
Sal77 Salary as of March 1975
Sex Sex of employee
Senior Seniority (months since first hired)
Age Age of employee (in months)
Educ Education (in years)
Exper Work experience prior to employment with the bank (months)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Roberts, H.V. (1979). Harris Trust and Savings Bank: An Analysis of Employee Compensation,
Report 7946, Center for Mathematical Studies in Business and Economics, University of Chicago
Graduate School of Business.
See Also
case0102
Examples
str(case1202)
pairs(Sal77~Bsal+Senior+Age+Exper, case1202)
case1301 25
case1301 Seaweed Grazers
Description
To study the influence of ocean grazers on regeneration rates of seaweed in the intertidal zone, a
researcher scraped rock plots free of seaweed and observed the degree of regeneration when certain
types of seaweed-grazing animals were denied access. The grazers were limpets (L), small fishes (f)
and large fishes (F). Each plot received one of six treatments named by which grazers were allowed
access. In addition, the researcher applied the treatments in eight blocks of 12 plots each. Within
each block she randomly assigned treatments to plots. The blocks covered a wide range of tidal
conditions.
Usage
case1301
Format
A data frame with 96 observations on the following 3 variables.
Cover percent of regenerated seaweed cover
Block a factor with levels "B1","B2","B3","B4","B5","B6","B7" and "B8"
Treat a factor indicating treatment, with levels "C","f","fF","L","Lf" and "LfF"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Olson, A. (1993). Evolutionary and Ecological Interactions Affecting Seaweeds, Ph.D. Thesis.
Oregon State University.
Examples
str(case1301)
# full two-way model with interactions
fitfull <- aov(Cover ~ Treat*Block, case1301)
# Residual plot indicates a transformation might help
plot(fitfull)
# Log of seaweed "regeneration ratio"
y <- with(case1301, log(Cover/(100-Cover)))
# Full two-way model with interactions
fitfull <- aov(y~Treat*Block, case1301)
# No problems indicated by residual plot
plot(fitfull)
# Note that interactions are not statistically significant
anova(fitfull)
# Additive model (no interactions)
26 case1302
fitadditive <- aov(y ~ Treat + Block, case1301)
# Make indicator variables for presence of limpets, small fish, and large fish
lmp <- with(case1301, ifelse(Treat %in% c("L", "Lf", "LfF"), 1, 0))
sml <- with(case1301, ifelse(Treat %in% c("f", "fF", "Lf", "LfF"), 1, 0))
big <- with(case1301, ifelse(Treat %in% c("fF", "LfF"), 1, 0))
fitsimple <- lm(y ~ Block + lmp + sml + big, case1301)
# Model with main effects of 3 "presence" factors seems ok.
anova(fitsimple, fitadditive)
summary(fitsimple, cor=FALSE)
case1302 Pygmalion Effect
Description
One company of soldiers in each of 10 platoons was assigned to a Pygmalion treatment group, with
remaining companies in the platoon assigned to a control group. Leaders of the Pygmalion pla-
toons were told their soldiers had done particularly well on a battery of tests which were, in fact,
non-existent. In this randomised block experiment, platoons are experimental units, companies are
blocks, and average Practical Specialty test score for soldiers in a platoon is the response. The re-
searchers wished to see if the platoon response was affected by the artificially-induced expectations
of the platoon leader.
Usage
case1302
Format
A data frame with 29 observations on the following 3 variables.
Company a factor indicating company identification, with levels "C1","C2",...,"C10"
Treat a factor indicating treatment with two levels, "Pygmalion" and "Control"
Score average score on practical specialty test of all soldiers in the platoon
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Eden, D. (1990). Pygmalion Without Interpersonal Contrast Effects: Whole Groups Gain from
Raising Manager Expectations, Journal of Applied Psychology 75(4): 395–398.
case1401 27
Examples
str(case1302)
# two-way model with interactions
fitfull <- aov(Score ~ Company*Treat, case1302)
# No problems are indicated by residual plot
plot(fitfull)
# Interaction terms are not statistically significant
anova(fitfull)
# Additive model, with "treatment contrast" for treatment:
fitadditive <- aov(Score ~ Company + Treat, case1302)
# Interpret treatment effect as coefficient of Treat
anova(fitadditive)
case1401 Chimp Learning Times
Description
Researchers taught each of 4 chimps to learn 10 words in American sign language and recorded the
learning time for each word for each chimp. They wished to describe chimp differences and word
differences.
Usage
case1401
Format
A data frame with 40 observations on the following 3 variables.
Minutes learning time in minutes
Chimp a factor indicating chimp, with four levels "Booee","Cindy","Bruno" and "Thelma"
Sign a factor indicating word taught, with 10 levels
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Fouts, R.S. (1973). Acquisition and Testing of Gestural Signs in Four Young Chimpanzees, Science
180: 978-980.
28 case1402
Examples
str(case1401)
fitadditive <- aov(Minutes ~ Chimp + Sign, case1401)
# Residual plot indicates a transformation may help
plot(fitadditive)
fitadditive <- aov(log(Minutes) ~ Chimp + Sign, case1401)
# No problems are indicated by residual plot
plot(fitadditive)
anova(fitadditive)
# Tukey multiple comparisons of sign differences
mcSign <- TukeyHSD(fitadditive,"Sign")
mcSign
plot(mcSign)
mcChimp <- TukeyHSD(fitadditive,"Chimp")
mcChimp
par(cex=.7)
plot(mcChimp)
case1402 Effect of Ozone, SO2 and Drought on Soybean Yield
Description
In a completely randomized design with a 2x3x5 factorial treatment structure, researchers randomly
assigned one of 30 treatment combinations to open-topped growing chambers, in which two soybean
cultivars were planted. The responses for each chamber were the yields of the two types of soybean.
Usage
case1402
Format
A data frame with 30 observations on the following 5 variables.
Stress a factor indicating treatment, with two levels "Well-watered" and "Stressed"
SO2 a quantitative treatment with three levels 0, 0.02 and 0.06
O3 a quantitative treatment with five levels 0.02, 0.05, 0.07, 0.08 and 0.10
Forrest the yield of the Forrest cultivar of soybean (in kg/ha)
William the yield of the Williams cultivar of soybean (in kg/ha)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
case1501 29
References
Heggestad, H.E. and Lesser, V.M. (1990). Effects of Chronic Doses of Sulfur Dioxide, Ozone,
and Drought on Yields and Growth of Soybeans Under Field Conditions, Journal of Environmental
Quality 19: 488–495.
Examples
str(case1402)
plot(Forrest ~ O3, case1402, log="y", pch=ifelse(Stress=="Stressed",19,21))
plot(Forrest ~ SO2, case1402, log="y", pch=ifelse(Stress=="Stressed",19,21))
fitbig <- lm(log(Forrest) ~ O3*SO2*Stress, case1402)
# Residual plot does not indicate any problem.
plot(fitbig)
# The 3-factor interaction is not statistically significant.
anova(fitbig)
# Drop the three-factor interaction
fit2 <- update(fitbig, ~ . - O3:SO2:Stress)
anova(fit2)
fitadditive <- lm(log(Forrest) ~ O3 + SO2 + Stress, case1402)
summary(fitadditive)
case1501 Logging and Water Quality
Description
Data from an observational study of nitrate levels measured at three week intervals for five years
in two watersheds. One of the watersheds was undisturbed and the other had been logged with a
patchwork pattern.
Usage
case1501
Format
A data frame with 88 observations on the following 3 variables.
Week week after the start of the study
Patch residual nitrate level in the logged watershed (ppm) (see Display 15.3 of Statistical Sleuth)
Nocut residual nitrate level in the undisturbed watershed (ppm)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
30 case1502
References
Harr, R.D., Friderksen, R.L., and Rothacher, J. (1979). Changes in Streamflow Following Timber
Harvests in Southwestern Oregon, USDA/USFS Research Paper PNW-249, Pacific NW Forest and
Range Experiment Station, Portland, Oregon.
Examples
str(case1501)
par(mfrow=c(2,1)) # Make 2 plots on one page
plot(Nocut ~ Week, case1501)
plot(Patch ~ Week, case1501)
par(mfrow=c(1,1))
lag.plot(case1501$Nocut,do.lines=FALSE)
lag.plot(case1501$Patch,do.lines=FALSE)
# Compute pooled estimate of first autocorrelation coefficient
# First auto covariance, Nocut
ac1nocut <- acf(case1501$Nocut,lag.max=1,type="covariance",plot=FALSE)$acf[2]
n <- length(case1501$Nocut)
# Zeroth autocovariance for Nocut
ac0nocut <- var(case1501$Nocut[2:n])*(n-2)/(n-1)
# First auto covariance, Patch
ac1patch <- acf(case1501$Patch,lag.max=1,type="covariance",plot=FALSE)$acf[2]
# Zeroth autocovariance for PATCH
ac0patch <- var(case1501$Patch [2:n])*(n-2)/(n-1)
ac1pool <- (ac1nocut + ac1patch)/2
ac0pool <- (ac0nocut + ac0patch)/2
acorr1 <- ac1pool/ac0pool
acorr1 # Pooled estimate of first lag serial coefficient
case1502 Global Warming
Description
The data are the temperatures (in degrees Celsius) averaged for the northern hemisphere over a
full year, for years 1880 to 1987. The 108-year average temperature has been subtracted, so each
observation is the temperature difference from the series average.
Usage
case1502
Format
A data frame with 108 observations on the following 2 variables.
Year year in which yearly average temperature was computed, from 1880 to 1987
Temp northern hemisphere temperature minus the 108-year average (degrees Celsius)
case1601 31
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Jones, P.D. (1988). Hemispheric Surface Air Temperature Variations—Recent Trends Plus an Up-
date to 1987, Journal of Climatology 1: 654–660.
Examples
str(case1502)
# Residuals from regression fit, ignoring autocorrelation
resids <- lm(Temp ~ Year, case1502)$res
# PACF plot shows evidence of 1st order auto correlation
acf(resids,type="partial")
# 1st autocorrelation coef.
acorr1 <- acf(resids,type="correlation",plot=FALSE)$acf[2]
# Fit regression with filtered response and explanatory variables:
n <- length(case1502$Temp)
y <- with(case1502, Temp [2:n] - acorr1* Temp [1:(n-1)])
x <- with(case1502, Year [2:n] - acorr1* Year [1:(n-1)])
fit <- lm(y ~ x)
summary(fit) # Interpret coefficient of x as coefficient of Year
case1601 Sites of Short- and Long-Term Memory
Description
Researchers taught 18 monkeys to distinguish each of 100 pairs of objects, 20 pairs each at 16, 12,
8, 4, and 2 weeks prior to a treatment. After this training, they blocked access to the hippocampal
formation in 11 of the monkeys. All monkeys were then tested on their ability to distinguish the ob-
jects. The five-dimensional response for each monkey is the number of correct objects distinguished
among those taught at 16, 12, 8, 4, and 2 weeks prior to treatment.
Usage
case1601
Format
A data frame with 18 observations on the following 7 variables.
Monkey Monkey name
Treatment a treatment factor with levels "Control" and "Treated"
Week2 percentage of 20 objects taught 2 weeks prior to treatment that were correctly distinguished
in the test
Week4 percentage of 20 objects taught 4 weeks prior to treatment that were correctly distinguished
in the test
32 case1602
Week8 percentage of 20 objects taught 8 weeks prior to treatment that were correctly distinguished
in the test
Week12 percentage of 20 objects taught 12 weeks prior to treatment that were correctly distin-
guished in the test
Week16 percentage of 20 objects taught 16 weeks prior to treatment that were correctly distin-
guished in the test
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Sola-Morgan, S. M. and Squire, L. R. (1990). The Primate Hippocampal Formation: Evidence for
a Time-limited Role in Memory Storage, Science 250: 288–290.
Examples
str(case1601)
# short-term response
short <- with(case1601, (Week2 + Week4)/2)
# long-term response
long <- with(case1601, (Week8 + Week12 + Week16)/3)
# Multivariate analysis of variance
mfit <- manova(cbind(short,long) ~ Treatment, case1601)
summary(mfit)
case1602 Oat Bran and Cholesterol
Description
In a randomized, double-blind, crossover experiment, researchers randomly assigned 20 volunteer
hospital employees to either a low-fiber or low-fiber treatment group. The subjects followed the
diets for six weeks. After two weeks on their normal diet, all patients crossed over to the other
treatment group for another six weeks. The total serum cholesterol (in mg/dl) was measured on
each patient before the first treatment, at the end of the first six week treatment, and at the end of
the second six week treatment.
Usage
case1602
Format
A data frame with 20 observations on the following 4 variables.
Baseline total serum cholesterol before treatment
Hifiber total serum cholesterol after the high fiber diet
Lofiber total serum cholesterol after the low fiber diet
Order factor to identify order of treatment, with two levels "HL" and "LH"
case1701 33
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Swain, J.F., Rouse, I.L., Curley, C.B., and Sacks, F.M. (1990). Comparison of the Effects of Oat
Bran and Low-fiber Wheat on Serum Lipoprotein Levels and Blood Pressure, New England Journal
of Medicine 320: 1746–1747.
Examples
str(case1602)
subjects <- 1:20
ordersubjects <- order(case1602$Baseline)
plot(1:20, case1602$Baseline[ordersubjects], pch=24,
xlab="Subjects (Ordered According to Baseline Cholesterol)",
ylab="Total Serum Cholesterol (mg/dl)")
points(1:20, case1602$Lofiber[ordersubjects], pch=19, col=5)
points(1:20, case1602$Hifiber[ordersubjects], pch=21, col=3)
legend(1,245,legend=c("Baseline","After Low Fiber Diet","After High Fiber Diet"),
pch=c(24,19,21),col=c(1,5,3))
diff <- with(case1602, Hifiber-Lofiber)
plot(subjects, diff, pch=ifelse(case1602$Order=="HL",19,21))
abline(h=0)
t.test(diff ~ Order, case1602) # Test for order of treatment effect
t.test(diff) # Test for treatment effect
case1701 Magnetic Force on Printer Rods
Description
Engineers manipulated three factors (with 3, 2, and 4 levels each) in the construction and operation
of printer rods, to see if they influenced the magnetic force around the rod.
Usage
case1701
Format
A data frame with 44 observations on the following 14 variables.
Name Description
L1,L2,..., L11 the magnetic force at each of the equally-spaces positions 1, 2, . . . , 11 on the printer rod
Current electric current passing through the rod, with three levels "0","250" and "500" (milliamperes)
Configur a factor identifying the configuration, with two levels "0" and "1"
Material a factor identifying the type of metal from which the rod was made, with four levels "1","2","3" and "4"
34 case1702
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(case1701)
pca <- princomp(case1701[,1:11])
summary(pca)
# The first 3 principal components account for 99.7% of the variation
screeplot(pca)
# The loadings suggest the following meaningful summaries...
loadings(pca)
overallaverage <- with(case1701, (L1 + L2 + L3 + L4 + L5 + L6 + L7 + L8 + L9 + L10 + L11)/11)
rightleftdiff <- with(case1701, (L9 + L10 + L11)/3 - (L1 + L2 + L3)/3)
middleleftdiff <- with(case1701, L6 - (L1 + L2)/2)
# Note 4 clusters and 1 outlier
pairs(cbind(overallaverage, rightleftdiff, middleleftdiff))
fit1 <- lm(overallaverage ~ Current*Configur*Material, case1701)
anova(fit1)
case1702 Love and Marriage
Description
Thirty couples participated in a study of love and marriage. Wives and husbands responded sepa-
rately to four questions:
1. What is the level of passionate love you feel for your spouse?
2. What is the level of passionate love your spouse feels for you?
3. What is the level of compassionate love you feel for your spouse?
4. What is the level of compassionate love your spouse feels for you?
Each response was recorded on a five-point scale: 1=None, 2=Very Little, 3=Some, 4=A Great Deal
and 5=A Tremendous Amount.
Usage
case1702
Format
A data frame with 30 observations on the following 9 variables.
Couple couple identification number
Hps level of passionate love husband feels for spouse
Wps level of passionate love wife feels for spouse
case1902 35
Hcs level of compassionate love husband feels for spouse
Wcs level of compassionate love wife feels for spouse
Hpy level of passionate love husband perceives spouse to have for him
Wpy level of passionate love wife perceives spouse to have for her
Hcy level of compassionate love husband perceives spouse to have for him
Wcy level of compassionate love husband perceives spouse to have for her
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Johnson, R.A. and Wichern, D.W. (1988). Applied Multivariate Statistical Analysis (2nd ed),
Prentice-Hall.
Examples
str(case1702)
# feelings about spouse
tospouse <- with(case1702, cbind(Hps, Wps, Hcs, Wcs))
# perceived feelings from spouse
fromspouse <- with(case1702, cbind(Hpy, Wpy, Hcy, Wcy))
cca <- cancor(tospouse,fromspouse)
# Examine loadings of first canonical variables:
par(mfrow=c(2,1))
barplot(cca$xcoef[,1], ylab="first 'to spouse'loadings",
names=c("Hps","Wps","Hcs","Wcs"))
barplot(cca$ycoef[,1], ylab="first 'from spouse'loadings",
names=c("Hpy","Wpy","Hcy","Wcy"))
# The first canonical variable for 'to spouse" is mostly Hcs
# The first canonical variable for 'fom spouse'is mostly Hcy
can.to <- tospouse
can.from <- fromspouse
can.to.1 <- can.to[,1] # first canonical variable
can.from.1 <- can.from[,1] # first canonical variable
pairs(cbind(can.to.1, case1702$Hcs, can.from.1, case1702$Hcy),
labels=c("1st cv 'to'","husband's compassionate","1st cv
'from'","husband's perceived compassionate"))
case1902 Death Penalty and Race
36 case1902
Description
Lawyers collected data on convicted black murderers in the state of Georgia to see whether con-
victed black murderers whose victim was white were more likely to receive the death penalty than
those whose victim was black, after accounting for aggravation level of the murder. They cate-
gorized murders into 6 progressively more serious types. Category 1 comprises barroom brawls,
liquor-induced arguments lovers’ quarrels, and similar crimes. Category 6 includes the most vi-
cious, cruel, cold=blooded, unprovoked crimes.
Usage
case1902
Format
A data frame with 12 observations on the following 4 variables.
Aggravation the aggravation level of the crime, a factor with levels "1","2","3","4","5" and
"6"
Victim a factor indicating race of murder victim, with levels "White" and "Black"
Death number in the aggravation and victim category who received the death penalty
Nodeath number in the aggravation and victim category who did not receive the death penalty
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Woodworth, G.C. (1989). Statistics and the Death Penalty, Stats 2: 9–12.
Examples
str(case1902)
# Add smidgeon to denominator because of zeros
empiricalodds <- with(case1902, Death/(Nodeath + .5))
plot(empiricalodds ~ as.numeric(Aggravation), case1902, log="y",
pch=ifelse(Victim=="White", 21, 19),
xlab="Aggravation Level of the Murder", ylab="Odds of Death Penalty")
legend(3.8,.02,legend=c("White Victim Murderers","Black Victim Murderers"),pch=c(21,19))
fitbig <- glm(cbind(Death,Nodeath) ~ Aggravation*Victim, case1902, family=binomial)
# No evidence of overdispersion; no statistically significant evidence
# of interactive effect
anova(fitbig, test="Chisq")
fitlinear <- glm(cbind(Death,Nodeath) ~ Aggravation + Victim, case1902, family=binomial)
summary(fitlinear)
# Mantel Haenszel Test, as an alternative
table1902 <- with(case1902, rbind(Death,Nodeath))
dim(table1902) <- c(2,2,6)
mantelhaen.test(table1902)
case2001 37
case2001 Survival in the Donner Party
Description
This data frame contains the ages and sexes of the adult (over 15 years) survivors and nonsurvivors
of the Donner party.
Usage
case2001
Format
A data frame with 45 observations on the following 3 variables.
Age Age of person
Sex Sex of person
Status Whether the person survived or died
Details
In 1846 the Donner and Reed families left Springfield, Illinois, for California by covered wagon.
In July, the Donner Party, as it became known, reached Fort Bridger, Wyoming. There its leaders
decided to attempt a new and untested rote to the Sacramento Valley. Having reached its full size of
87 people and 20 wagons, the party was delayed by a difficult crossing of the Wasatch Range and
again in the crossing of the desert west of the Great Salt Lake. The group became stranded in the
eastern Sierra Nevada mountains when the region was hit by heavy snows in late October. By the
time the last survivor was rescued on April 21, 1847, 40 of the 87 members had died from famine
and exposure to extreme cold.
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Grayson, D.K. (1990). Donner Party Deaths: A Demographic Assessment, Journal of Anthropo-
logical Research 46: 223–242.
See Also
ex1918
Examples
str(case2001)
38 case2002
case2002 Birdkeeping and Lung Cancer
Description
A 1972–1981 health survey in The Hague, Netherlands, discovered an association between keeping
pet birds and increased risk of lung cancer. To investigate birdkeeping as a risk factor, researchers
conducted a case–control study of patients in 1985 at four hospitals in The Hague (population
450,000). They identified 49 cases of lung cancer among the patients who were registered with a
general practice, who were age 65 or younger and who had resided in the city since 1965. They
also selected 98 controls from a population of residents having the same general age structure.
Usage
case2002
Format
A data frame with 147 observations on the following 7 variables.
LC Whether subject has lung cancer
FM Sex of subject
SS Socioeconomic status, determined by occupation of the household’s principal wage earner
BK Indicator for birdkeeping (caged birds in the home for more that 6 consecutive months from 5
to 14 years before diagnosis (cases) or examination (control))
AG Age of subject (in years)
YR Years of smoking prior to diagnosis or examination
CD Average rate of smoking (in cigarettes per day)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Holst, P.A., Kromhout, D. and Brand, R. (1988). For Debate: Pet Birds as an Independent Risk
Factor for Lung Cancer, British Medical Journal 297: 13–21.
Examples
str(case2002)
case2101 39
case2101 Island Size and Bird Extinctions
Description
In a study of the Krunnit Islands archipelago, researchers presented results of extensive bird surveys
taken over four decades. They visited each island several times, cataloguing species. If a species
was found on a specific island in 1949, it was considered to be at risk of extinction for the next
survey of the island in 1959. If it was not found in 1959, it was counted as an “extinction”, even
though it might reappear later. This data frame contains data on island size, number of species at
risk to become extinct and number of extinctions.
Usage
case2101
Format
A data frame with 18 observations on the following 4 variables.
Island Name of Island
Area Area of Island
Atrisk Number of species at risk
Extinct Number of extinctions
Details
Scientists agree that preserving certain habitats in their natural states is necessary to slow the accel-
erating rate of species extinctions. But they are divided on how to construct such reserves. Given a
finite amount of available land, is it better to have many small reserves or a few large one? Central
to the debate on this question are observational studies of what has happened in island archipelagos,
where nearly the same fauna tries to survive on islands of different sizes.
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
V\"ais\"anen, R.A. and J\"arvinen, O. (1977). Dynamics of Protected Bird Communities in a
Finnish Archipelago, Journal of Animal Ecology 46: 891–908.
Examples
str(case2101)
logit <- function(p) log(p/(1-p))
plot(logit(Extinct/Atrisk) ~ log(Area), case2101)
40 case2102
case2102 Moth Coloration and Natural Selection
Description
This data was collected by J.A. Bishop. Bishop selected seven locations progressively farther from
Liverpool. At each location, Bishop chose eight trees at random. Equal number of dead (frozen)
light (Typicals) and dark (Carbonaria) moths were glued to the trunks in lifelike positions. After
24 hours, a count was taken of the numbers of each morph that had been removed—presumably by
predators.
Usage
case2102
Format
A data frame with 14 observations on the following 4 variables.
Morph Morph, a factor with levels "light" and "dark"
Distance Distance from Liverpool (in km)
Placed Number of moths placed
Removed Number of moths removed
Details
Population geneticists consider clines particularly favourable situations for investigating evolution-
ary phenomena. A cline is a region where two colour morphs of one species arrange themselves at
opposite ends of an environmental gradient, with increasing mixtures occurring between. Such a
cline exists near Liverpool, England, where a dark morph of a local moth has flourished in response
to the blackening of tree trunks by air pollution from the mills. The moths are nocturnal, resting
during the day on tree trunks, where their coloration acts as camouflage against predatory birds. In
Liverpool, where tree trunks are blackened by smoke, a high percentage of the moths are of the dark
morph. One encounters a higher percentage of the typical (pepper–and–salt) morph as one travels
from the city into the Welsh countryside, where tree trunks are lighter. J.A. Bishop used this cline
to study the intensity of natural selection.
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Bishop, J.A. (1972). An Experimental Study of the Cline of Industrial Melanism in Biston betularia
[Lepidoptera] Between Urban Liverpool and Rural North Wales, Journal of Animal Ecology 41:
209–243.
Examples
str(case2102)
case2201 41
case2201 Age and Mating Success of Male Elephants
Description
Although male elephants are capable of reproducing by 14 to 17 years of age, your adult males
are usually unsuccessful in competing with their larger elders for the attention of receptive females.
Since male elephants continue to grow throughout their lifetimes, and since larger males tend to be
more successful at mating, the males most likely to pass their genes to future generations are those
whose characteristics enable them to live long lives. Joyce Poole studied a population of African
elephants in Amboseli National Park, Kenya, for 8 years. This data frame contains the number of
successful matings and ages (at the study’s beginning) of 41 male elephants.
Usage
case2201
Format
A data frame with 41 observations on the following 2 variables.
Age Age of elephant at beginning of study
Matings Number of successful matings
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Poole, J.H. (1989). Mate Guarding, Reproductive Success and Female Choice in African Elephants,
Animal Behavior 37: 842–849.
Examples
str(case2201)
plot(case2201)
case2202 Characteristics Associated with Salamander Habitat
Description
The Del Norte Salamander (plethodon elongates) is a small (5–7 cm) salamander found among rock
rubble, rock outcrops and moss-covered talus in a narrow range of northwest California. To study
the habitat characteristics of the species and particularly the tendency of these salamanders to reside
in dwindling old-growth forests, researchers selected 47 sites from plausible salamander habitat in
national forest and parkland. Randomly chosen grid points were searched for the presence of a site
with suitable rocky habitat. At each suitable site, a 7 metre by 7 metre search are was examined for
the number of salamanders it contained. This data frame contains the counts of salamanders at the
sites, along with the percentage of forest canopy and age of the forest in years.
42 ex0112
Usage
case2202
Format
A data frame with 47 observations on the following 4 variables.
Site Investigated site
Salaman Number of salamanders found in 49 m$^2$ area
PctCover Percentage of canopy cover
Forestage Forest age
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Welsh, H.H. and Lind, A.J. (1995). Journal of Herpetology 29(2): 198–210.
Examples
str(case2202)
ex0112 Fish Oil and Blood Pressure
Description
Researchers used 7 red and 7 black playing cards to randomly assign 14 volunteer males with high
blood pressure to one of two diets for four weeks: a fish oil diet and a standard oil diet. These data
are the reductions in diastolic blood pressure.
Usage
ex0112
Format
A data frame with 14 observations on the following 2 variables.
BP reduction in diastolic blood pressure (in mm of mercury)
Diet factor variable indicating the diet that the subject followed
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
ex0116 43
References
Knapp, H.R. and FitzGerald, G.A. (1989). The Antihypertensive Effects of Fish Oil, New England
Journal of Medicine 320: 1037–1043.
Examples
str(ex0112)
ex0116 Planet Distances and Order from Sun
Description
The data are the distances from the sun (scaled so that earth=10) and the order from the sun for the
9 planets in our solar system plus the asteroid belt (treated here as the fifth body from the sun).
Usage
ex0116
Format
A data frame with 10 observations on the following 3 variables.
Planet name of body (planet or asteroid belt)
Order order from sun
Distance distance from sun (scaled so that earth’s distance is 10)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(ex0116)
44 ex0221
ex0211 Lifetimes of Guinea Pigs
Description
The data are survival times (in days) of guinea pigs that were randomly assigned either to a control
group or to a treatment group that received a dose of tubercle bacilli.
Usage
ex0211
Format
A data frame with 122 observations on the following 2 variables.
Lifetime survival time of guinea pig (in days)
Group a factor with levels "bacilli" and "control", indicating the group to which the guinea pig
was assigned
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Doksum, K. (1974). Empirical Probability Plots and Statistical Inference for Nonlinear Models in
the Two–sample Case, Annals of Statistics 2: 267–277.
Examples
str(ex0211)
ex0221 Bumpus’s Data on Natural Selection (Weight)
Description
As evidence in support of natural selection, Bumpus presented measurements on house sparrows
brought to the Anatomical Laboratory of Brown University after an uncommonly severe winter
storm. Some of these birds had survived and some had perished. Bumpus asked whether those that
perished did so because they lacked physical characteristics enabling them to withstand the intensity
of that particular instance of selective elimination. The data are on the the weights, in grams, for
the 24 adult male sparrows that perished and for the 35 adult males that survived.
Usage
ex0221
ex0222 45
Format
A data frame with 59 observations on the following 2 variables.
Weight weight of adult male sparrows (in grams)
Status factor variable indicating whether the sparrow perished or survived in a winter storm
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
case0201,ex2016
Examples
str(ex0221)
ex0222 Cholesterol in Urban and Rural Guatemalans
Description
This data comes from an observational study to contrast cholesterol levels in rural and urban
Guatemalan Indians
Usage
ex0222
Format
A data frame with 94 observations on the following 2 variables.
Cholesterol Serum total cholesterol of individual (in mg/l)
Group a factor with levels "Rural" and "Urban" indicating to which group the individual belongs
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Tejada, C., Charm, S., Guzman, M., Mendez, J. and Kurland, G. (1964). The Blood Viscosity of
Various Socioeconomic Groups in Guatemala, American Journal of Clinical Nutrition: 303–308.
Examples
str(ex0222)
46 ex0321
ex0223 Speed Limits and Traffic Fatalities
Description
The National Highway System Designation Act was signed into law in the United States on Novem-
ber 28, 1995. Among other things, the act abolished the federal mandate of 55 mile per hour max-
imum speed limits on roads in the United States and permitted states to establish their own limits.
Of the 50 states (plus the District of Columbia), 32 increased their speed limits at the beginning of
1996 or sometime during 1996. These data are the percentage changes in interstate highway traffic
fatalities from 1995 to 1996.
Usage
ex0223
Format
A data frame with 51 observations on the following 3 variables.
State US state
Increase a factor with levels "No" "Yes", indicating whether the state increased its speed limit
FatalitiesChange percentage change in interstate traffic fatalities between 1995 and 1996
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Report to Congress: The Effect of Increased Speed Limits in the Post-NMSL Era, National High-
way Traffic Safety Administration, February, 1998; available in the reports library at http://
www-fars.nhtsa.dot.gov/.
Examples
str(ex0223)
ex0321 Umpire Life Lengths
Description
Researchers collected historical and current data on umpires to investigate their life expectancies
following the collapse and death of a U.S. major league baseball umpire. They were investigating
speculation that stress associated with the job posed a health risk. Data were found on 227 umpires
who had died or had retired and were still living. The data set includes the dates of birth and death.
ex0323 47
Usage
ex0321
Format
A data frame with 227 observations on the following 3 variables.
Lifelength observed lifetime for those umpires who had died by the time of the study or current
age of those still living
Censored 0 for those who had died by the time of the study or 1 for those who were still living
Expected length from actuarial life tables for individuals who were alive at the time the person
first became an umpire
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Cohen, R.S., Kamps, C.A., Kokoska, S., Segal E.M. and Tucker, J.B.(2000). Life Expectancy of
Major League Baseball Umpires, The Physician and Sportsmedicine 28(5): 83–89.
Examples
str(ex0321)
ex0323 Solar Radiation and Skin Cancer
Description
Data contains yearly skin cancer rates (per 100,000 people) in Connecticut from 1938 to 1972 with
a code indicating those years that came two years after higher than average sunspot activity and
those years that came two years after lower than average sunspot activity.
Usage
ex0323
Format
A data frame with 35 observations on the following 3 variables.
Year year
Rate skin cancer rate per 100,000 people
Sunspot a factor with levels "High" and "Low"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
48 ex0327
References
Andrews, D.F. and Herzberg, A.M. (1985). Data: A Collection of Problems from many Fields for
the Student and Research Worker, Springer-Verlag.
Examples
str(ex0323)
ex0327 Life Expectancy and Per Capita Income
Description
Life expectancy and per capita income for 20 industrialized countries and 9 petroleum exporting
countries. Note that there is a missing value for South Africa.
Usage
ex0327
Format
A data frame with 29 observations on the following 4 variables.
Country a character vector indicating the country
Life life expectancy (years)
Income income in 1974 (U.S. dollars)
Type factor variable with levels "Industrialized" and "Petroleum"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Leinhardt, S. and Wasserman, S.S. (1979). Teaching Regression: An Exploratory Approach, The
American Statistician 33(4): 196–203.
Examples
str(ex0327)
ex0328 49
ex0328 Pollen Removal
Description
As part of a study to investigate reproductive strategies in plants, biologists recorded the time spent
at sources of pollen and the proportions of pollen removed by bumblebee queens and honeybee
workers pollinating a species of lily.
Usage
ex0328
Format
A data frame with 47 observations on the following 3 variables.
Removed proportion of pollen removed
Duration duration of visit (in seconds)
Bee factor variable with levels "Queen" and "Worker"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Harder, L.D. and Thompson, J.D. (1989). Evolutionary Options for Maximizing Pollen Dispersal
of Animal-pollinated Plants, American Naturalist 133: 323–344.
Examples
str(ex0328)
ex0331 Iron Supplementation
Description
A randomized experiment was performed on mice to determine whether two forms of iron are
retained differently. If one type is retained especially well it may be more useful as a dietary
supplement for humans.
Usage
ex0331
50 ex0332
Format
A data frame with 36 observations on the following 2 variables.
Iron percentage of iron retained in each mouse
Supplement factor variable with levels "Fe3" and "Fe4"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Rice, J. (1987). Mathematical Statistics and Data Analysis, Wadsworth.
Examples
str(ex0331)
ex0332 College Tuition
Description
Tuition in dollars of 20 private and 20 public U.S. colleges and universities for 1993–1994.
Usage
ex0332
Format
A data frame with 20 observations on the following 3 variables.
Private tuition in dollars of 20 private schools
PubIn tuition in dollars of 20 public schools (in-state tuition)
PubOut tuition in dollars of 20 public schools (out-of-state tuition)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
1995 U.S. News and World Report’s Guide to America’s Best Colleges.
Examples
str(ex0332)
ex0333 51
ex0333 Brain Size and Litter Size
Description
Relative brain weights for 51 species of mammal whose average litter size is less than 2 and for 45
species of mammal whose average litter size is greater than or equal to 2.
Usage
ex0333
Format
A data frame with 96 observations on the following 2 variables.
Brainsize relative brain sizes (1000 * Brain weight/Body weight) for 96 species of mammals
Littersize factor variable with levels "Small" and "Large"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Sacher, G.A. and Staffeldt, E.F. (1974). Relation of Gestation Time to Brain Weight for Placental
Mammals: Implications for the Theory of Vertebrate Growth, American Naturalist 108: 593–613.
See Also
case0902
Examples
str(ex0333)
ex0428 Darwin’s Data
Description
Plant heights (inches) for 15 pairs of plants of the same age, one of which was grown from a seed
from a cross-fertilized flower and the other of which was grown from a seed from a self-fertilized
flower.
Usage
ex0428
52 ex0429
Format
A data frame with 15 observations on the following 2 variables.
Cross height (inches) of cross-fertilized plant
Self height (inches) of self-fertilized plant
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Andrews, D.F. and Herzberg, A.M. (1985). Data: A Collection of Problems from many Fields for
the Student and Research Worker, Springer-Verlag.
Examples
str(ex0428)
ex0429 Exercise and Walking Time
Description
Can active exercise shorten the time it takes an infant to walk alone? Twelve, one week old, male
infants from white, middle-class families were randomly allocated to one of two treatment groups.
Those in the active-exercise group received stimulation of the walking reflexes during four 3 minute
sessions each day from the beginning of the second through the end of the eighth week. Those in
the other group received no stimulation.
Usage
ex0429
Format
A data frame with 12 observations on the following 2 variables.
Age age (months) at which infants first walked alone
Exercise a factor with levels "Active" and "None"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Zelazo, P.R. (1972). Walking in the Newborn, Science 176: 314–315.
Examples
str(ex0429)
ex0430 53
ex0430 Sunlight Protection Factor
Description
Tolerance to sunlight (in minutes) for 13 patients prior to and after treatment with a sunscreen.
Usage
ex0430
Format
A data frame with 13 observations on the following 2 variables.
Control tolerance to sunlight (minutes) prior to sunscreen application
Sunscreen tolerance to sunlight (minutes) after sunscreen application
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Fusaro, R.M. and Johnson, J.A. (1974). Sunlight Protection for Erythropoietic Protoporphyria Pa-
tients, Journal of the American Medical Association 229(11): 1420.
Examples
str(ex0430)
ex0431 Effect of Group Therapy on Survival of Breast Cancer Patients
Description
Researchers randomly assigned metastatic breast cancer patients to either a control group or a group
that received weekly 90 minute sessions of group therapy and self-hypnosis, to see whether the latter
treatment improved the patients’ quality of life.
Usage
ex0431
Format
A data frame with 58 observations on the following 3 variables.
Survival months of survival after beginning of study
Group a factor with levels "Control" and "Therapy"
Censor 0 if entire lifetime observed, 1 if patient known to have lived at least 122 months
54 ex0432
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Spiegel, D., Bloom, J.R., Kraemer, H.C. and Gottheil, E. (1989). Effect of Psychosocial Treatment
on Survival of Patients with Metastatic Breast Cancer, Lancet 334(8668): 888–891.
Examples
str(ex0431)
ex0432 Therapeutic Marijuana
Description
To investigate the capacity of marijuana to reduce the side effects of cancer chemotherapy, re-
searchers performed a double-blind, randomized, crossover trial. Fifteen cancer patients on chemother-
apy were randomly assigned to receive either a marijuana treatment or a placebo treatment after their
first three sessions of chemotherapy. They were then crossed over to the opposite treatment for their
next 3 sessions.
Usage
ex0432
Format
A data frame with 15 observations on the following 3 variables.
Subject subject number 1–15
Marijuana total number of vomiting and retching episodes under marijuana treatment
Placebo total number of vomiting and retching episodes under placebo treatment
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Chang, A.E., Shiling, D.J., Stillman, R.C., Goldberg, N.H., Seipp, C.A., Barofsky, I., Simon, R.M.
and Rosenberg, S.A. (1979). Delta-9-Tetrahydrocannabinol as an Antiemetic in Cancer Patients
Receiving High Dose Methotrexate, Annals of Internal Medicine 91(6): 819–824.
Examples
str(ex0432)
ex0518 55
ex0518 Fatty Acid
Description
A randomized experiment was performed to estimate the effect of a certain fatty acid CPFA on the
level of a certain protein in rat livers.
Usage
ex0518
Format
A data frame with 30 observations on the following 4 variables.
Protein levels of protein (x 10) found in rat livers
Treatment a factor with levels "Control","CPFA50","CPFA150","CPFA300","CPFA450" and
"CPFA600"
Day a factor with levels "Day1","Day2","Day3","Day4" and "Day5"
Group a factor with levels "Group1","Group2",...,"Group10"; the observed levels of the Treatment
and Day interaction
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(ex0518)
ex0523 Was Tyrannosaurus Rex Warm-Blooded?
Description
Data frame with measurements of oxygen isotopic composition of vertebrate bone phosphate (per
mil deviations from SMOW) in 12 bones of a singe Tyrannosaurus rex specimen
Usage
ex0523
Format
A data frame with 52 observations on the following 2 variables.
Oxygen oxygen isotopic composition
Bonegrp a factor with levels "Bone1","Bone2",...,"Bone12"
56 ex0524
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Barrick, R.E. and Showers, W.J. (1994). Thermophysiology of Tyrannosaurus rex: Evidence from
Oxygen Isotopes, Science 265(5169): 222–224.
See Also
ex1120
Examples
str(ex0523)
ex0524 Vegetarians and Zinc: An Observational Study
Description
Previous studies suggest that vegetarians may not receive enough zinc in their diets and the zinc re-
quirement is especially important during pregnancy. Twenty-three women were monitored: twelve
vegetarians who were pregnant, six nonvegetarians who were pregnant, and five vegetarians who
were not pregnant. Is there any evidence that pregnant vegetarians tend to have lower zinc levels
than pregnant nonvegetarians?
Usage
ex0524
Format
A data frame with 23 observations on the following 2 variables.
Zinc levels of Zinc (µg/g) in the hair of women
Group a factor with levels "PregNonVeg","PregVeg" and "NonPregVeg"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
King, J.C., Stein, T. and Doyle, M. (1981). Effect of Vegetarianism on the Zinc Status of Pregnant
Women, American Journal of Clinical Nutrition 34(6): 1049–1055.
Examples
str(ex0524)
ex0621 57
ex0621 Failure Times of Bearings
Description
Data consist of times to fatigue failure (in units of millions of cycles) for 10 high-speed turbine
engine bearings made from five different compounds.
Usage
ex0621
Format
A data frame with 50 observations on the following 2 variables.
Time failure times of bearings (millions of cycles)
Compound a factor with levels "I","II","III","IV" and "V"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
McCool, J.I. (1979). Analysis of Single Classification Experiments Based on Censored Samples
from the Two-parameter Weibull Distribution, Journal of Statistical Planning and Inference 3(1):
39–68.
Examples
str(ex0621)
ex0622 A Biological Basis for Homosexuality
Description
Is there a physiological basis for sexual preference? Researchers measured the volumes of four cell
groups in the interstitial nuclei of the anterior hypothalamus in postmortem tissue from 41 subjects
at autopsy from seven metropolitan hospitals in New York and California.
Usage
ex0622
58 ex0622
Format
A data frame with 41 observations on the following 2 variables.
Volume volumes of INAH3 (1000 ×mm3) cell clusters from 41 humans
Group a factor with levels
ex0723 59
"Group1" heterosexual male with AIDS death
"Group2" heterosexual male with Non-AIDS death
"Group3" homosexual male with AIDS death
"Group4" heterosexual female with AIDS death
"Group5" heterosexual female with Non-AIDS death
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
LeVay, S. (1991). A Difference in Hypothalamic Structure Between Heterosexual and Homosexual
Men, Science 253(5023): 1034–1037.
Examples
str(ex0622)
ex0723 Old Faithful
Description
Old Faithful Geyser in Yellowstone National Park, Wyoming, derives its name and its considerable
fame from the regularity (and beauty) of its eruptions. As they do with most geysers in the park,
rangers post the predicted tiems of eruptions on signs nearby and people gather beforehand to wit-
ness the show. R.A. Hutchinson, a park geologist, collected measurements of the eruption durations
(X, in minutes) and the subsequent intervals before the next eruption (Y, in minutes) over an 8–day
period.
Usage
ex0723
Format
A data frame with 107 observations on the following 3 variables.
Date date of observation (August 1 to August 8, 1978)
Interval length of interval before the next eruption (in minutes)
Duration duration of eruption (in minutes)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Weisberg, S. (1985). Applied Linear Regression, John Wiley \& Sons, New York, p. 231.
60 ex0724
Examples
str(ex0723)
ex0724 Crab Claw Size and Force
Description
As part of a study of the effects of predatory intertidal crab species on snail populations, researchers
measured the mean closing forces and the propdus heights of the claws on several crabs of three
species.
Usage
ex0724
Format
A data frame with 38 observations on the following 3 variables.
Force closing strength of claw of the crab
Height propodus height of claw of the crab
Species species to which the crab belongs
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Yamada, S.B. and Boulding, E.G. (1992). Shell–breaking Efficiency of Predatory Crabs Influences
the Distribution of an Intertidal Snail, Technical Report, Zoology Department, Oregon State Uni-
versity.
Examples
str(ex0724)
ex0726 61
ex0726 Decline in Male Births
Description
The data are on the proportion of male birts in Denmark, The Netherlands, Canada and the United
States for a number of yeras. Notice that the proportions for Canada and the United States are only
provided for the years 1970 to 1990, while Denmark and The Netherlands have data listed for 1950
to 1994.
Usage
ex0726
Format
A data frame with 45 observations on the following 5 variables.
Year year of observation
Denmark male birth rate of Denmark for given year
Netherlands male birth rate of The Netherlands for given year
Canada male birth rate of Canada for given year
Usa male birth rate of the United States for given year
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Davis, D.L., Gottlieb, M.B. and Stampnitzky, J.R. (1998). Reduced ratio of male to female births
in several industrial countries, Journal of the American Medical Association 279(13): 1018–1023.
Examples
str(ex0726)
ex0727 The Big Bang II
Description
These data are measured distances and recession velocities for 10 clusters of nebulae, much farther
from earth than the nebulae reported in case0701.
Usage
ex0727
62 ex0728
Format
A data frame with 10 observations on the following 2 variables.
Cluster name of the cluster of nebulae
Distance distance from earth (in million parsec)
Velocity recession velocity (in kilometres per second)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Hubble, E. and Humason, M. (1931). The Velocity–Distance Relation Among Extra–calactic Neb-
ulae, Astrophysics Journal 74: 43–50.
See Also
case0701
Examples
str(ex0727)
ex0728 Number of Stories and Building Height
Description
The 1994 World Almanac reports heights and number of stories for notable tall buildings in North
America. The data in this data frame are a random sample of size 60 of those for which dates of
completion were available.
Usage
ex0728
Format
A data frame with 60 observations on the following 3 variables.
Year year of completion
Height height of building
Stories number of stories of building
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(ex0728)
ex0729 63
ex0729 Male Displays
Description
Black wheatears are small birds in Spain and Morocco. Males of the species demonstrate an ex-
aggerated sexual display by carrying many heavy stones to nesting cavities. This 35–gram bird
transports, on average, 3.1 kg of stones per nesting season! Different males carry somewhat differ-
ent sized stones, prompting a study on whether larger stones may be a signal of higher health status.
Soler et al. calculated the average stone mass (g) carried by each of 21 male black wheatears, along
with T-cell response measurements reflecting their immune systems’ strengths.
Usage
ex0729
Format
A data frame with 21 observations on the following 2 variables.
Mass average mass of stones carried by bird (in g)
Tcell T-cell response measurement (in mm)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Soler, M., Martín-Vivaldi, M., Marín J. and Møller, A. (1999). Weight lifting and health status in
the black wheatears, Behavioral Ecology 10(3): 281–286.
Examples
str(ex0729)
ex0730 Brain Activity in Violin and String Players
Description
Studies over the past two decades have shown that activity can effect the reorganisation of the human
central nervous system. For example, it is known that the part of the brain associated with activity
of a finger or limb is taken over for other purposes in individuals whose limb or finger has been lost.
In one study, psychologists used magnetic source imaging (MSI) to measure neuronal activity in the
brains of nine string players (six violinists, two cellists and one guitarist) and six controls who had
never played a musical instrument, when the thumb and fifth finger of the left hand were exposed
to mild stimulation. The researchers felt that stringed instrument players, who use the fingers of
their left hand extensively, might show different behaviour—as a result of this extensive physical
activity—than individuals who did not play stringed instruments.
64 ex0816
Usage
ex0730
Format
A data frame with 15 observations on the following 2 variables.
Years years that the individual has been playing
Activity neuronal activity index
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Elbert, T., Pantev, C., Wienbruch, C., Rockstroh, B. and Taub E. (1995). Increased cortical repre-
sentation of the fingers of the left hand in string players, Science 270(5234): 305–307.
Examples
str(ex0730)
ex0816 Meat Processing
Description
The data in case0702 are a subset of the complete data on postmortum pH in 12 steer carcasses.
Usage
ex0816
Format
A data frame with 12 observations on the following 2 variables.
Time time after slaughter (hours)
pH pH level in postmortem muscle
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Schwenke, J.R. and Milliken, G.A. (1991). On the Calibration Problem Extended to Nonlinear
Models, Biometrics 47(2): 563–574.
ex0817 65
See Also
case0702
Examples
str(ex0816)
ex0817 Biological Pest Control
Description
In a study of the effectiveness of biological control of the exotic weed tansy ragwort, researchers
manipulated the exposure to the ragwort flea beetle on 15 plots that had been planted with a high
density of ragwort. Harvesting the plots the next season, they measured the average dry mass of
ragwort remaining (grams/plant) and the flea beetle load (beetles/gram of ragwort dry mass) to see
if the ragwort plants in plots with high flea beetle loads were smaller as a result of herbivory by the
beetles.
Usage
ex0817
Format
A data frame with 15 observations on the following 2 variables.
Load flee beetle load (in beetles/gram of ragwort dry mass)
Mass dry mass of ragwort weed
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
McEvoy, P. and Cox, C. (1991). Successful Biological Control of Ragwort, Senecio jacobaea, by
introducing insects in Oregon, Ecological Applications 1(4): 430–442.
Examples
str(ex0817)
66 ex0820
ex0818 Chernobyl Fallout
Description
One of the most dangerous contaminants deposited over European countries following the Cher-
nobyl accident in April 1986 was radioactive cesium. To study cesium transfer from contaminated
soil to plants, researchers collected soil samples and samples of mushroom mycelia from 17 wooded
locations in Umbria, Central Italy, from August 1986 to November 1989. The data are measured
concentrations (Bq/kg) of cesium in the soil and in the mushrooms.
Usage
ex0818
Format
A data frame with 17 observations on the following 2 variables.
Mushroom Cesium concentrations in mushrooms (in Bq/kg)
Soil Cesium concentrations in soil (in Bq/kg)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Borio, R., Chiocchini, S., Cicioni, R., Degli Esposti, P., Rongoni, A., Sabatini, P., Scampoli, P.,
Antonini, A. and Salvadori, P. (1991). Uptake of Radiocesium by Mushrooms, Science of the Total
Environment 106(3): 183–190.
Examples
str(ex0818)
ex0820 Election Fraud
Description
The data are observations on the difference between Democratic and Republican vote counts, by (a)
absentee ballot and (b) voting machine, for 21 elections in Philadelphia’s senatorial districts over
the last 10 years.
Usage
ex0820
ex0822 67
Format
A data frame with 21 observations on the following 2 variables.
Absentee Democratic minus Republican vote count by absentee ballot
Machines Democratic minus Republican vote count by voting machine
Details
In a special election to fill a Pennsylvania State Senate seat in 1993, the Democrat, William Stinson,
received 19,127 machine–counted votes and the Republican, Bruce Marks, received 19,691. In
addition, there were 1,391 absentee ballots for Stinson and 366 absentee ballots for Marks, so that
the total tally showed Stinson the winner by 461 votes. The large disparity between the machine–
counted and absentee votes, and the resulting reversal of the outcome due to the absentee ballots
caused some concern about possible illegal influence on the absentee votes. To see whether the
discrepancy in absentee votes was larger than could be explained by chance, an econometrician
considered the data given in this data frame (read from a graph in The New York Times, 11 April
1994).
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
ex1115
Examples
str(ex0820)
ex0822 Ecosystem Decay
Description
Data are the number of butterfly species in 16 islands of forest of various sizes in otherwise cleared
areas in Brazil.
Usage
ex0822
Format
A data frame with 16 observations on the following 2 variables.
Area area (ha) of forest patch
Species number of butterfly species
68 ex0823
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Lovejoy, T.E., Rankin, J.M., Bierregaard, Jr., R.O., Brown, Jr., K.S., Emmons, L.H. and van der
Voort, M. (1984). Ecosystem decay of Amazon forest remnants in Nitecki, M.H. (ed.) Extinctions,
University of Chicago Press.
Examples
str(ex0822)
ex0823 Wine Consumption and Heart Disease
Description
The data are the average wine consumption rates (in liters per person per year) and number of
ischemic heart disease deaths (per 1000 men aged 55 to 64 years) for 18 industrialized countries.
Usage
data(ex0823)
Format
A data frame with 18 observations on the following 3 variables.
Country a character vector indicating the country
Wine consumption of wine (liters per person per year)
Mortality heart disease mortality rate (deaths per 1,000)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
St. Leger A.S., Cochrane, A.L. and Moore, F. (1979). Factors Associated with Cardiac Mortality in
Developed Countries with Particular Reference to the Consumption of Wine, Lancet: 1017–1020.
Examples
str(ex0823)
ex0824 69
ex0824 Respiratory Rates for Children
Description
A high respiratory rate is a potential diagnostic indicator of respiratory infection in children. To
judge whether a respiratory rate is “high” however, a physician must have a clear picture of the
distribution of normal rates. To this end, Italian researchers measured the respiratory rates of 618
children between the ages of 15 days and 3 years.
Usage
ex0824
Format
A data frame with 618 observations on the following 2 variables.
Age age in months of child
Rate respiratory rate (breaths per minute)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Rusconi, F., Castagneto, M., Porta, N., Gagliardi, L., Leo, G., Pellegatta, A., Razon, S. and Braga,
M. (1994). Reference Values for Respiratory Rate in the First 3 Years of Life, Pediatrics 94(3):
350–355.
Examples
str(ex0824)
ex0825 The Dramatic U.S. Presidential Election of 2000
Description
Data set shows the number of votes for Buchanan and Bush in all 67 counties in Florida during the
U.S. presidential election of November 7, 2000.
Usage
ex0825
70 ex0914
Format
A data frame with 67 observations on the following 3 variables.
County a character vector indicating the county
Buchanan2000 votes cast for P. Buchanan
Bush2000 votes cast for G.W. Bush
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
ex1222
Examples
str(ex0825)
ex0914 Pace of Life and Heart Disease
Description
In four regions of the US (Northeast, Midwest, South and West), in three different sized metropoli-
tan regions, researchers measured indicators of pace of life.
Usage
ex0914
Format
A data frame with 36 observations on the following 4 variables.
Bank bank clerk speed
Walk pedestrian walking speed
Talk postal clerk talking speed
Heart age adjusted death rate due to heart disease
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Levine, R.V. (1990). The Pace of Life, American Scientist 78: 450–459.
Examples
str(ex0914)
ex0915 71
ex0915 Rainfall and Corn Yield
Description
Data on corn yield and rainfall in six U.S. corn–producing states (Iowa, Nebraska, Illinois, Indiana,
Missouri and Ohio), recorded for each year from 1890 to 1927.
Usage
ex0915
Format
Year year of observation (1890–1927)
Yield average corn yield for the six states (in bu/acre)
Rainfall average rainfall in the six states (in in/year)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Ezekiel, M. and Fox, K.A. (1959). Methods of Correlation and Regression Analysis, John Wiley \&
Sons, New York.
Examples
str(ex0915)
ex0918 Speed of Evolution
Description
Researchers studied the development of a fly (Drosophila subobscura) that had been accidentally
introduced from the Old World into North America around 1980.
Usage
ex0918
72 ex0920
Format
A data frame with 21 observations on the following 8 variables.
Continent a factor with levels "NA" and "EU"
Latitude latitude (degrees)
Females average wing size (103×log mm) of female flies on log scale
SE.F standard error of wing size (103×log mm) of female flies on log scale
Males average wing size (103×log mm) of male flies on log scale
SE.M standard error of wing size (103×log mm) of male flies on log scale
Ratio average basal length to wing size ratios of female flies
SE.R standard error of average basal length to wing size ratio of female flies
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Huey, R.B., Gilchrist, G.W., Carlson, M.L., Berrigan, D. and Serra, L. (2000). Rapid Evolution of
a Geographic Cline in Size in an Introduced Fly, Science 287(5451): 308–309.
Examples
str(ex0918)
ex0920 Winning Speeds at the Kentucky Derby
Description
Data set contains the year of the Kentucky Derby, the winning horse, the condition of the track and
the average speed of the winner for years 1896–2000.
Usage
ex0920
Format
A data frame with 105 observations on the following 4 variables.
Year year of Kentucky Derby
Winner a character vector with the name of the winning horse
Condition a factor with levels "fast","good" and "slow"
Speed average speed of the winner (feet per second)
ex1014 73
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
http://www.kentuckyderby.com
Examples
str(ex0920)
ex1014 Toxic Effects of Copper and Zinc
Description
Researchers randomly allocated 25 beakers containing minnow larvae to receive one of 25 treatment
combinations of 5 levels of zinc and 5 levels of copper.
Usage
ex1014
Format
A data frame with 25 observations on the following 3 variables.
Copper amount of copper received (in ppm)
Zinc amount of zinc received (in ppm)
Protein protein in minnow larvae exposed to copper and zinc (µg/larva)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Ryan, D.A., Hubert, J.J., Carter, E.M., Sprague, J.B. and Parrott, J. (1992). A Reduced-Rank
Multivariate Regression Approach to Aquatic Joint Toxicity Experiments, Biometrics 48(1): 155–
162.
Examples
str(ex1014)
74 ex1027
ex1026 Thinning of Ozone Layer
Description
Depletion of the ozone layer allows the most damaging ultraviolet radiation to reach the Earth’s
surface. To measure the relationship, researchers sampled the ocean column at various depths at 17
locations around Antarctica during the austral spring of 1990.
Usage
ex1026
Format
A data frame with 17 observations on the following 3 variables.
Inhibit percent inhibition of primary phytoplankton production in water
UVB UVB exposure
Surface a factor with levels "Deep" and "Surface"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Smith, R.C., Prézelin, B.B., Baker, K.S., Bidigare, R.R., Boucher, N.P., Coley, T., Karentz, D., Mac-
Intyre, S., Matlick, H.A., Menzies, D., Ondrusek, M., Wan, Z. and Waters, K.J. (1992). Ozone De-
pletion: Ultraviolet Radiation and Phytoplankton Biology in Antarctic Waters, Science 255(5047):
952–959.
Examples
str(ex1026)
ex1027 Factors Affecting Extinction
Description
Data are measurements on breeding pairs of land-bird species collected from 16 islands around
Britain over the course of several decades. For each species, the data set contains an average time
of extinction on those islands where it appeared, the average number of nesting pairs, the size of the
species and the migratory status of the species.
Usage
ex1027
ex1028 75
Format
A data frame with 62 observations on the following 5 variables.
Species a character vector indicating the species
Time average extinction time in years
Pairs average number of nesting pairs
Size a factor with levels "L" and "S"
Status a factor with levels "M" and "R"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Pimm, S.L., Jones, H.L., and Diamond, J. (1988). On the Risk of Extinction, American Naturalist
132(6): 757–785.
Examples
str(ex1027)
ex1028 El Nino and Hurricanes
Description
Data set with the numbers of Atlantic Basin tropical storms and hurricanes for each year from 1950–
1997. The variable storm index is an index of overall intensity of hurricane season. Also listed are
whether the year was a cold, warm or neutral El Nino year and a variable indicating whether West
Africa was wet or dry that year.
Usage
ex1028
Format
A data frame with 48 observations on the following 7 variables.
Year year
ElNino a factor with levels "cold","neutral" and "warm"
Temperature numeric variable with values -1 if ElNino is "cold", 0 if "neutral" and 1 if "warm"
WestAfrica numeric variable indicating whether West Africa was wet (1) or dry (0)
Storms number of storms
Hurricanes number of hurricanes
StormIndex index of overall intensity of hurricane season
76 ex1029
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Data were gathered by William Gray of Colorado State University and reported on USA Today
weather page: http://www.usatoday.com/weather/whurnum.htm
Examples
str(ex1028)
ex1029 Wage and Race
Description
Data set contains weekly wages in 1987 for a sample of 25,632 males between the age of 18 and 70
who worked full-time along with their years of education, years of experience, indicator variable
for whether they were black, indicator variable for whether they worked in or near a city, and a code
for the region in the US where they worked.
Usage
ex1029
Format
A data frame with 25631 observations on the following 6 variables.
Wage weekly wage in dollars
Education education in years
Experience experience in years
Black a factor with levels "Yes" and "No"; indicator for whether the person is black
SMSA a factor with levels "Yes" and "No"; indicator for whether the person worked in or near a city
Region a factor with levels "MW","NE","S" and "W"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Bierens, H.J. and Ginther, D.K. (2001). Integrated Conditional Moment Testing of Quantile Re-
gression Models, Empirical Economics 26(1): 307–324
http://econ.la.psu.edu/~hbierens/QUANTILE.PDF
http://econ.la.psu.edu/~hbierens/MEDIAN.HTM
ex1115 77
Examples
str(ex1029)
ex1115 Election Fraud
Description
The data are observations on the difference between Democratic and Republican vote counts, by (a)
absentee ballot and (b) voting machine, for 22 elections in Philadelphia’s senatorial districts over
the last 10 years.
Usage
ex1115
Format
A data frame with 22 observations on the following 2 variables.
Absentee Democratic minus Republican vote count by absentee ballot
Machines Democratic minus Republican vote count by voting machine
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
ex0820
Examples
str(ex1115)
ex1120 Was Tyrannosaurus Rex Warm-Blooded?
Description
Data are the isotopic composition of structural bone carbonate (X) and the isotopic composition
of the coexisting calcite cements (Y) in 18 bone samples from a specimen of the dinosaur Tyran-
nosaurus rex. Evidence that the mean of Yis positively associated with Xwas used in an argument
that the metabolic rate of this dinosaur resembled warm-blooded more than cold-blooded animals.
Usage
ex1120
78 ex1122
Format
A data frame with 18 observations on the following 2 variables.
Carbonat isotopic composition of bone carbonate
Calcite isotopic composition of calcite cements
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Barrick, R.E. and Showers, W.J. (1994). Thermophysiology of Tyrannosaurus rex: Evidence from
Oxygen Isotopes, Science 265(5169): 222–224.
See Also
ex0523
Examples
str(ex1120)
ex1122 Deforestation and Debt
Description
It has been theorized that developing countries cut down their forests to pay off foreign debt. Data
are debt, deforestation, and population from 11 Latin American nations.
Usage
ex1122
Format
A data frame with 11 observations on the following 4 variables.
Country a character vector indicating the country
Debt debt (millions of dollars)
Deforest deforestation (thousands of ha)
Pop population (thousands of people)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
ex1123 79
References
Gullison, R.R. and Losos, E.C. (1992). The Role of Foreign Debt in Deforestation in Latin America,
Conservation Biology 7(1): 140–7.
Examples
str(ex1122)
ex1123 Air Pollution and Mortality
Description
Does pollution kill people? Data in one early study designed to explore this issue from 5 Standard
Metropolitan Statistical Areas in the U.S between 1959–1961.
Usage
ex1123
Format
A data frame with 60 observations on the following 7 variables.
City a character vector indicating the city
Mort total age-adjusted mortality from all causes
Precip mean annual precipitation (inches)
Educ median number of school years completed for persons 25 years or older
Nonwhite percentage of population that is nonwhite
NOx relative pollution potential of oxides of nitrogen
SO2 relative pollution potential of sulfur dioxide
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
McDonald, G.C. and Ayers, J.A. (1978). Some Applications of the “Chernoff Faces”: A Technique
for Graphically Representing Multivariate Data in Wang, P.C.C. (ed.) Graphical Representation of
Multivariate Data, Academic Press.
See Also
ex1217
Examples
str(ex1123)
80 ex1217
ex1124 Natal Dispersal Distances of Mammals
Description
An assessment of the factors affecting dispersal distances is important for understanding population
spread, recolonization and gene flow which are central issues for conservation of many vertebrate
species. Researchers gathered data on body weight, diet type and maximum natal dispersal distance
for various animals.
Usage
ex1124
Format
A data frame with 64 observations on the following 4 variables.
Species a character vector indicating the species
Bodymass bodymass (kg)
Maxdist maximum dispersal distance (km)
Type a factor with levels "Carnivore","Herbivore" and "Omnivore"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Sutherland, G.D., Harestad, A.S., Price, K. and Lertzman, K.P. (2000). Scaling of Natal Dispersal
Distances in Terrestrial Birds and Mammals, Conservation Ecology 4(1): 16.
Examples
str(ex1124)
ex1217 Pollution and Mortality
Description
Complete data set for problem introduced in ex1123. Data from early study designed to explore the
relationship between air pollution and mortality.
Usage
ex1217
ex1217 81
Format
A data frame with 60 observations on the following 17 variables.
City a character vector indicating the city
Mort total age-adjusted mortality from all causes
Precip mean annual precipitation (inches)
Humidity percent relative humidity (annual average at 1:00pm)
Jantemp mean January temperature (degrees F)
Julytemp mean July temperature (degrees F)
Over65 percentage of the population aged 65 years or over
House population per household
Educ median number of school years completed for persons 25 years or older
Sound percentage of the housing that is sound with all facilities
Density population density (in persons per square mile of urbanized area)
Nonwhite percentage of population that is nonwhite
Whitecol percentage of employment in white collar occupations
Poor percentage of households with annual income under $3,000 in 1960
HC relative pollution potential of hydrocarbons
NOx relative pollution potential of oxides of nitrogen
SO2 relative pollution potential of sulfur dioxide
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
McDonald, G.C. and Ayers, J.A. (1978). Some Applications of the “Chernoff Faces”: A Technique
for Graphically Representing Multivariate Data in Wang, P.C.C. (ed.) Graphical Representation of
Multivariate Data, Academic Press.
See Also
ex1123
Examples
str(ex1217)
82 ex1220
ex1220 Galapagos Islands
Description
The number of species on an island is known to be related to the island’s area. Of interest is what
other variables are also related to the number of species, after island area is accounted for, and
whether the answer differs for native and non native species.
Usage
ex1220
Format
A data frame with 30 observations on the following 8 variables.
Island a character vector indicating the island
Total total number of observed species
Native number of native species
Area area (km2)
Elev elevation (m)
DistNear distance from nearest island (km)
DistSC distance from Santa Cruz (km)
AreaNear area of nearest island (km2)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Johnson, M.P. and Raven, P.H. (1973). Species Number and Endemism: The Galapagos Archipelago
Revisited, Science 179(4076): 893–895.
Examples
str(ex1220)
ex1221 83
ex1221 River Nitrogen
Description
The rise in abundance of algae in coastal waters is thought to be due to increases in nutrients such
as nitrate and other forms of nitrogen. Researchers gathered data to gauge the evidence that nitrates
in the discharges of rivers around the world are associated with human population density.
Usage
ex1221
Format
A data frame with 42 observations on the following 11 variables.
River a character vector indicating the river
Country a factor variable with 26 levels
Discharge the estimated annual average discharge of the river into an ocean (m3per second)
Runoff estimated annual average runoff from the watershed (liters/(sec×km2))
Area watershed area (km2)
Density density of people (people/km2)
NO3 nitrate concentration (µM/l)
Export nitrate export (product of runoff times nitrate concentration)
Dep deposition (proportional to product of nitratrate precipitation times precipitation)
NPrec nitrate precipitation (µmol NO3/(sec×km2))
Prec precipitation (cm/year)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Cole, J.L., Peierls, B.L., Caraco, N.F. and Pace, M.L. (1993). Nitrogen Loading of Rivers as a
Human-driven Process, in McDonnell, M.J. and Pickett, S.T.A. (eds.) Humans as Components of
Ecosystems: The Ecology of Subtle Human Effects and Populated Areas, Springer-Verlag.
Examples
str(ex1221)
84 ex1222
ex1222 Bush Gore Ballot Controversy
Description
This data set contains the vote counts by county in Florida for Buchanan and for four other pres-
idential candidates in 2000, along with the total vote counts in 2000, the presidential vote counts
for three presidential candidates in 1996, the vote count for Buchanan in his only other campaign
in Florida—the 1996 Republican primary, the registration in Buchanan’s Reform party and the total
political party registration in the county.
Usage
ex1222
Format
A data frame with 67 observations on the following 13 variables.
County a character vector indicating the county
Buchanan2000 votes cast for Buchanan in 2000 presidential election
Gore2000 votes cast for Gore in 2000 presidential election
Bush2000 votes cast for Bush in 2000 presidential election
Nader2000 votes cast for Nader in 2000 presidential election
Browne2000 votes cast for Browne in 2000 presidential election
Total2000 total vostes cast in 2000 presidential election
Clinton96 votes cast for Clinton in 1996 presidential election
Dole96 votes cast for Dole in 1996 presidential election
Perot96 votes cast for Perot in 1996 presidential election
Buchanan96p votes cast for Buchanan in 1996 Republican primary
ReformReg the registration in Buchanan’s Reform party
TotalReg the total political party registration
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
ex0825
Examples
str(ex1222)
ex1317 85
ex1317 Dinosaur Extinctions—An Observational Study
Description
About 65 million years ago, the dinosaurs suffered a mass extinction virtually overnight (in geologic
time). Among many clues, one that all scientists regard as crucial is a layer of iridium-rich dust that
was deposited over much of the earth at that time. The theory is that an event like a volcanic eruption
or meteor impact caused a massive dust cloud that blanketed the earth for years killing off animals
and their food sources. Dataset has Iridium depths by type of deposit.
Usage
ex1317
Format
A data frame with 28 observations on the following 3 variables.
Iridium Iridium in samples (ppt)
Strata a factor with levels "Limestone" and "Shale"
Depth a factor with six levels: "1","2",...,"6"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Alvarez, W. and Asaro, F. (1990). What Caused the Mass Extinction? An Extraterrestrial Impact,
Scientific American 263(4): 76–84.
Courtillot, E. (1990). What Caused the Mass Extinction? A Volcanic Eruption. Scientific American
263(4): 85–92.
Examples
str(ex1317)
ex1319 Nature—Nurture
Description
A 1989 study investigated the effect of heredity and environment on intelligence. Data are the IQ
scores for adopted children whose biological and adoptive parents were categorized either in the
highest or the lowest socioeconomic status category.
86 ex1320
Usage
ex1319
Format
A data frame with 38 observations on the following 3 variables.
IQ IQ scores of adopted children
Adoptive a factor with levels "High" and "Low"; the socioeconomic status of the adoptive parents
Biologic a factor with levels "High" and "Low"; the socioeconomic status of the biological parents
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Capron, C. and Duyme, M. (1991). Children’s IQ’s and SES of Biological and Adoptive Parents in
a Balanced Cross-fostering Study, European Bulletin of Cognitive Psychology 11(3): 323–348.
See Also
ex1605
Examples
str(ex1319)
ex1320 Gender Differences in Performance on Mathematics Achievement
Tests
Description
Data set on 861 ACT Assessment Mathematics Usage Test scores from 1987. The test was given to
a sample of high school seniors who met one of three profiles of high school mathematics course
work: (a) Algebra I only; (b) two Algebra courses and Geometry; and (c) two Algebra courses,
Geometry, Trigonometry, Advanced Mathematics and Beginning Calculus.
These data were generated from summary statistics for one particular form of the test as reported
by Doolittle (1989).
Usage
ex1320
Format
A data frame with 861 observations on the following 3 variables.
Sex a factor with levels "female" and "male"
Background a factor with levels "a","b" and "c"
Score ACT mathematics test score
ex1414 87
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Doolittle, A.E. (1989). Gender Differences in Performance on Mathematics Achievement Items,
Applied Measurement in Education 2(2): 161–177.
Examples
str(ex1320)
ex1414 Blood Brain Barrier
Description
Researchers designed an experiment to investigate how delivery of brain cancer antibody is influ-
enced by tumor size, antibody molecular weight, blood-brain barrier disruption, and delivery route.
Usage
ex1414
Format
A data frame with 36 observations on the following 6 variables.
Agent a factor with levels "AIB","DEX7" and "MTX"
Treatment a factor with levels "BD" and "NS"
Route a factor with levels "IA" and "IV"
Days days after inoculation
BAT concentration of antibody in the part of the brain around the tumor
LH concentration of antibody in the unaffected part of the brain
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Barnett, P.A., Roman-Goldstain, S., Ramsey, F., McCormick, C.I., Sexton, G., Szumowski, J. and
Neuwelt, E.A. (1995). Differential Permeability and Quantitative MR Imaging of a Human Lung
Carcinoma Brain Xenograft in the Nude Rat, American Journal of Pathology 146(2): 436–449.
See Also
ex1415
88 ex1415
Examples
str(ex1414)
ex1415 Second Replicate of the Barrier Disruption Study
Description
Researchers designed an experiment to investigate how delivery of brain cancer antibody is influ-
enced by tumor size, antibody molecular weight, blood-brain barrier disruption, and delivery route.
The data for the first replicate of this study is in ex1414. This is the second replicate for the study.
Usage
ex1415
Format
A data frame with 36 observations on the following 6 variables.
Agent a factor with levels "AIB","DEX7" and "MTX"
Treatment a factor with levels "BD" and "NS"
Route a factor with levels "IA" and "IV"
Days days after inoculation
BAT concentration of antibody in the part of the brain around the tumor
LH concentration of antibody in the unaffected part of the brain
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Barnett, P.A., Roman-Goldstain, S., Ramsey, F., McCormick, C.I., Sexton, G., Szumowski, J. and
Neuwelt, E.A. (1995). Differential Permeability and Quantitative MR Imaging of a Human Lung
Carcinoma Brain Xenograft in the Nude Rat, American Journal of Pathology 146(2): 436–449.
See Also
ex1414
Examples
str(ex1415)
ex1417 89
ex1417 Tennessee Corn Yield Trials
Description
Corn yield trials were performed at four locations in Tennessee in 1999. Data shows the average
yields for six hybrids at each of four locations.
Usage
ex1417
Format
A data frame with 30 observations on the following 3 variables.
Location a factor with five levels: "Ames.irr","Ames.un","Crossvill","Knoxville" and
"Milan"
Hybrid a factor with six levels: "AsgrowRX799","Beck5912W","Cargill7821","FFR739W",
"NorthrupKing" and "Pioneer"
Yield average yield (bushels per acre)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
University of Tennessee Agricultural Experiment Station.
Examples
str(ex1417)
ex1509 Sunspot Counts for 1749–1948
Description
Time series data set of annual counts of sunspots.
Usage
ex1509
Format
A data frame with 200 observations on the following 2 variables.
Year year
Spots number of sunspots
90 ex1512
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Waldmeier, M. (1961). The Sunspot Activity in the Years 1610–1960, Federal Observatory, Zurich.
Examples
str(ex1509)
ex1512 Melanoma and Sunspot Activity—An Observational Study
Description
Several factors suggest that the incidence of melanoma is related to solar radiation. Data has the
age-adjusted melanoma incidence among males from Connecticut Tumor Registry, 1936–1972.
Usage
ex1512
Format
A data frame with 37 observations on the following 3 variables.
Year year
Melanoma male melanoma incidence in number of cases per 100,000 population
Sunspot sunspot relative number
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Houghton, A., Munster, E.W. and Viola, M.V. (1978). Increased Incidence of Malignant Melanoma
After Peaks of Sunspot Activity, Lancet: 759–760.
Examples
str(ex1512)
ex1513 91
ex1513 Lynx Trappings and Sunspots
Description
Data on the annual numbers of lynx trapped in the Mackenzie River district of northwest Canada
from 1821–1934.
Usage
ex1513
Format
A data frame with 114 observations on the following 3 variables.
Year year
Lynx number of lynx trapped
Spots number of sunspots
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Elston, C. and Nicholson, M. (1942). The Ten Year Cycle in Numbers of the Lynx in Canada,
Journal of Animal Ecology 11(2): 215–244.
Examples
str(ex1513)
ex1514 Trends in Firearm and Motor Vehicle Deaths in the U.S.
Description
Data shows the number of deaths due to firearms and the number of deaths due to motor vehicle
accidents in the United States between 1968 and 1993.
Usage
ex1514
92 ex1515
Format
A data frame with 26 observations on the following 3 variables.
Year year
FirearmDeaths deaths due to firearms (in thousands per year)
MotorVehicleDeaths deaths due to motor vehicles (in thousands per year)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Data read from a Centers for Disease Control and Prevention graph reported in The Oregonian, June
17, 1997.
Examples
str(ex1514)
ex1515 S\&P 500
Description
Data on the value of a $1 U.S. stock investment in 1871 at the end of each year, based on the
Standard and Poor (S&P) 500 Composite stock index.
Usage
ex1515
Format
A data frame with 129 observations on the following 2 variables.
Year year
SPReturn S&P composite stock index ($)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(ex1515)
ex1605 93
ex1605 Nature—Nurture
Description
Data are a subset from an observational, longitudinal, study on adopted children. Is child’s intelli-
gence related to intelligence of the biological mother and the intelligence of the adoptive mother?
Usage
ex1605
Format
A data frame with 62 observations on the following 6 variables.
AMED adoptive mother’s years of education
BMIQ biological mother’s score on IQ test
Age2IQ IQ of child at age 2
Age4IQ IQ of child at age 4
Age8IQ IQ of child at age 8
Age13IQ IQ of child at age 13
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Skodak, M. and Skeels, H.M. (1949). A Final Follow-up Study of One Hundred Adopted Children,
Journal of Genetic Psychology 75: 85–125.
See Also
ex1319
Examples
str(ex1605)
94 ex1612
ex1611 Religious Competition
Description
Adam Smith, in Wealth of Nations, observed that even religious monopolies become weak when
they are not challenged by competition. Data to illustrate this point is from 21 countries in which
the percentages of Catholics in the populations varied from a low 1.2% to a high 97.6%.
Usage
ex1611
Format
A data frame with 21 observations on the following 4 variables.
Country a character vector indicating the country
PctCath percent Catholics in the population
P2PRatio priest to parishioner ratio
PctIndig percent clergy indigenous
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Gill, A.J. (1994). Rendering unto Caesar? Religious Competition and Catholic Political Strategy in
Latin America, 1962–79, American Journal of Political Science 38(2): 403–425.
Examples
str(ex1611)
ex1612 Wastewater
Description
Samples of effluent were divided and sent to two laboratories for testing. Data are measurements of
biochemical oxygen demand and suspended solid measurements obtained for 2 sample splits from
the two laboratories.
Usage
ex1612
ex1613 95
Format
A data frame with 11 observations on the following 4 variables.
ComBOD biochemical oxygen demand measurements from commercial laboratory
ComSS suspended solids measurements from commercial laboratory
StaBOD biochemical oxygen demand measurements from state laboratory
StaSS suspended solids measurements from state laboratory
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Johnson, R.A. and Wichern, D.W. (1988). Applied Multivariate Statistical Analysis, Prentice-Hall.
Examples
str(ex1612)
ex1613 Flea Beetle Distinction
Description
Data are the measurements from two very similar species of flea beetle.
Usage
ex1613
Format
A data frame with 36 observations on the following 3 variables.
Jnt1 measurement of first joint in micrometers
Jnt2 measurement of second joint in micrometers
Species a factor with levels "conc" and "heik"
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Lubischew, A.A. (1962). On the Use of Discriminant Functions in Taxonomy, Biometrics 18: 455–
477.
Examples
str(ex1613)
96 ex1615
ex1614 Pschoimmunology
Description
Recent studies in the field of psychoimmunology suggest a link exists between behavioral events
and the functioning of one’s immune system. Data shows the results of a study on 12 subjects who
were monitored during three distinct activities. The first activity consisted of neutral activity such
as reporting tasks. During the second activity, subjects listened to audiotape exercises relating to
images of heaviness, warmth in the body, relaxation, suggestions to remember happy events, etc.
The third activity included a nonaudio tape follow up stimulus consisting of continued relaxation as
in activity 2 and a verbal discussion of the positive aspects of the audiotape.
Usage
ex1614
Format
A data frame with 12 observations on the following 3 variables.
PhaseA Interleukin-1 levels (counts per minute) from blood samples taken during activity A
PhaseB Interleukin-1 levels (counts per minute) from blood samples taken during activity B
PhaseC Interleukin-1 levels (counts per minute) from blood samples taken during activity C
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Keppel, W. (1993). Effects of Behavioral Stimuli on Plasma Interleukin-1 Activity in Humans at
Rest, Journal of Clinical Psychology 49(6): 777–785.
Examples
str(ex1614)
ex1615 Trends in SAT Scores
Description
Data shows a partial listing of a data set with ratios of average math to average verbal SAT scores
in the United States and the District of Columbia for 1989 and 1996–1999.
Usage
ex1615
ex1708 97
Format
A data frame with 51 observations on the following 6 variables.
State a character vector indicating the state
M/V:89 average MATH SAT scores divided by average VERBAL SAT score in 1989
M/V:96 average MATH SAT scores divided by average VERBAL SAT score in 1996
M/V:97 average MATH SAT scores divided by average VERBAL SAT score in 1997
M/V:98 average MATH SAT scores divided by average VERBAL SAT score in 1998
M/V:99 average MATH SAT scores divided by average VERBAL SAT score in 1999
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(ex1615)
ex1708 Pig Fat
Description
Actual pig fat and measurements of pig fat from magnetic resonance images at 13 locations for 12
pigs.
Usage
ex1708
Format
A data frame with 12 observations on the following 14 variables.
Fat actual pig fat (in percent)
M1 magnetic resonance image at location 1
M2 magnetic resonance image at location 2
M3 magnetic resonance image at location 3
M4 magnetic resonance image at location 4
M5 magnetic resonance image at location 5
M6 magnetic resonance image at location 6
M7 magnetic resonance image at location 7
M8 magnetic resonance image at location 8
M9 magnetic resonance image at location 9
M10 magnetic resonance image at location 10
M11 magnetic resonance image at location 11
M12 magnetic resonance image at location 12
M13 magnetic resonance image at location 13
98 ex1713
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Glasbey, C.A and Flowler, P.A. (1992). Regression Models Fitted Using Conditional Independence
to Estimate Pig Fatness from Magnetic Resonance Images, The Statistician 41(2): 179–184.
Examples
str(ex1708)
ex1713 Church Distinctiveness
Description
Data show measures that differ among denominations of American Protestant and Catholic churches.
Usage
ex1713
Format
A data frame with 18 observations on the following 6 variables.
Denomination a character vector indicating the church denomination
Distinct distinctiveness (strictness of discipline on a seven point scale)
Attend average percentage of weeks that individuals attended a church meeting (% weekly)
NonChurch average number of secular organisations to which members belong
StrongPct average percentage of members that describe themselves as being strong church mem-
bers (%)
AnnInc average income of members (US$)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Iannaccone, L.R. (1994). Why Strict Churches Are Strong, American Journal of Sociology 99(5):
1180–1211.
Examples
str(ex1713)
ex1714 99
ex1714 Insurance
Description
In the 1970’s the U.S. Commission on Civil Rights investigated charges that insurance companies
were attempting to redefine Chicago “neighborhoods” in order to cancel existing homeowner in-
surance policies or refuse to issue new ones. Dataset has data on homeowner and residential fire
insurance policy issuances from 47 zip codes in the Chicago area.
Usage
ex1714
Format
A data frame with 47 observations on the following 8 variables.
Zip last 2 digits of zip code
Fire fires per 1000 housing units
Theft thefts per 1000 population
Age percentage of housing units built prior to 1940
Income median family income
Race percentage minority
Vol number of new policies per 100 housing units
Invol number of FAIR plan policies and renewals per 100 housing units
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Andrews, D.F. and Herzberg, A.M. (1985). Data: A Collection of Problems from many Fields for
the Student and Research Worker, Springer-Verlag.
Examples
str(ex1714)
100 ex1916
ex1914 Mantel-Haenszel Test for Censored survival Times: Lymphoma and
Radiation Data
Description
Survival times for two groups of lymphoma patients.
Usage
ex1914
Format
A data frame with 34 observations on the following 4 variables.
Months months after diagnosis
Group a factor with levels "no" and "radiation"
Survived number of patients known to survive beyond this month
Died number of patients known to die after this many months
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Neuwelt, E.A., Goldman, D.L., Dahlborg, S.A., Crossen, J., Ramsey, F., Roman-Goldstein, S.,
Braziel, R. and Dana, B. (1991). Primary CNS Lymphoma Treated with Osmotic Blood-brain
Barrier Disruption: Prolonged Survival and Preservation of Cognitive Function, Journal of Clinical
Oncology 9(9): 1580–1590.
Examples
str(ex1914)
ex1916 Vitamin C and Colds
Description
Fictitious data set based on results of an experiment where subjects were randomly divided into
two groups and given a placebo or vitamin c to take during the cold season. At the end of the cold
season, the subjects were interviewed by a physician who determined whether they had or had not
suffered a cold during the period. Skeptics interviewed the 800 subjects to determine who knew and
who did not know to which group they had been assigned. Vitamin C has a bitter taste and those
familiar with it could recognize whether their pills contained it.
ex1917 101
Usage
ex1916
Format
A data frame with 4 observations on the following 4 variables.
Knew a factor with levels "no" and "yes"
Treatment a factor with levels "placebo" and "vitC"
Cold number of people who got a cold
NoCold number of people who did not get a cold
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(ex1916)
ex1917 Alcohol Consumption and Breast Cancer—A Retrospective Study
Description
Dataset from a study which investigated the added risk of breast cancer due to alcohol consumption.
A sample of confirmed breast cancer patients were compared with a sample of cancer free women
who were close in age and from the same neighborhood as the cases. Data was collected on the
alcohol consumption and body mass of both sets of women.
Usage
ex1917
Format
A data frame with 6 observations on the following 4 variables.
Bodymass a factor with levels "high","low" and "medium"
Drinking a factor with levels "high" and "low"
Cases number of women with breast cancer
Controls number of women without breast cancer
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
102 ex1918
References
Rosenberg, L., Palmer, J.R., Miller, D.R., Clarke, E.A. and Shapiro, S. (1990). A Case-Control
Study of Alcoholic Beverage Consumption and Breast Cancer, American Journal of Epidemiology
131(1): 6–14.
Examples
str(ex1917)
ex1918 The Donner Party
Description
In 1846 the Donner party became stranded while crossing the Sierra Nevada Mountains near Lake
Tahoe. The data frame has the counts for male and female survivors for six age groups.
Usage
ex1918
Format
A data frame with 12 observations on the following 4 variables.
Age a factor with six levels: "15-19","20-29","30-39","40-49","50-59" and "60-69"
Sex a factor with levels "female" and "male"
Lived number that lived
Died number that died
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Grayson, D.K. (1990). Donner Party Deaths: A Demographic Assessment, Journal of Anthropo-
logical Research 46: 223–242.
See Also
case2001
Examples
str(ex1918)
ex1919 103
ex1919 Tire-Related Fatal Accidents and Ford Sports Utility Vehicles
Description
Data shows the numbers of compact sports utility vehicles involved in fatal accidents in the U.S.
between 1995 and 1999, categorized according to travel speed, make of car (Ford or other), and
cause of accident (tire-related or other).
Usage
ex1919
Format
A data frame with 8 observations on the following 4 variables.
Speed a factor with levels "0-40","41-55","56-65" and ">65"
Make a factor with levels "Ford" and "Other"
Other cause of accident was other than tire-related
Tire cause of accident was tire-related
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
ex2018
Examples
str(ex1919)
ex2011 Space Shuttle
Description
This data frame contains the launch temperatures (degrees Fahrenheit) and an indicator of O-ring
failures for 24 space shuttle launches prior to the space shuttle Challenger disaster of January 28,
1986.
Usage
ex2011
104 ex2012
Format
A data frame with 24 observations on the following 2 variables.
Temp Launch temperature (in degrees Fahrenheit)
Failure Indicator of O-ring failure
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
case0401,ex2223
Examples
str(ex2011)
ex2012 Muscular Dystrophy
Description
Duchenne Muscular Dystrophy (DMD) is a genetically transmitted disease, passed from a mother
to her children. Boys with the disease usually die at a young age; but affected girls usually do
not suffer symptoms, may unknowingly carry the disease and may pass it to their offspring. It is
believed that about 1 in 3,300 women are DMD carriers. A woman might suspect she is a carrier
when a related male child develops the disease. Doctors must rely on some kind of test to detect
the presence of the disease. This data frame contains data on two enzymes in the blood, creatine
kinase (CK) and hemopexin (H) for 38 known DMD carriers and 82 women who are not carriers. It
is desired to use these data to obtain an equation for indicating whether a women is a likely carrier.
Usage
ex2012
Format
A data frame with 120 observations on the following 3 variables.
Group Indicator whether the woman has DMD ("Case") or not ("Control")
CK Creatine kinase reading
HHemopexin reading
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
ex2015 105
References
Andrews, D.F. and Herzberg, A.M. (1985). Data: A Collection of Problems From Many Fields For
The Student And Research Worker, Springer-Verlag, New York.
Examples
str(ex2012)
ex2015 Spotted Owl Habitat
Description
A study examined the association between nesting locations of the Northern Spotted Owl and avail-
ability of mature forests. Wildlife biologists identified 30 nest sites. The researchers selected 30
other sites at random coordinates in the same forest. On the basis of aerial photographs, the per-
centage of mature forest (older than 80 years) was measured in various rings around each of the 60
sites.
Usage
ex2015
Format
A data frame with 60 observations on the following 8 variables.
Site Site, a factor with levels "Random" and "Nest"
PctRing1 Percentage of mature forest in ring with outer radius 0.91 km
PctRing2 Percentage of mature forest in ring with outer radius 1.18 km
PctRing3 Percentage of mature forest in ring with outer radius 1.40 km
PctRing4 Percentage of mature forest in ring with outer radius 1.60 km
PctRing5 Percentage of mature forest in ring with outer radius 1.77 km
PctRing6 Percentage of mature forest in ring with outer radius 2.41 km
PctRing7 Percentage of mature forest in ring with outer radius 3.38 km
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Ripple W.J., Johnson, D.H., Thershey, K.T. and Meslow E.C. (1991). Old–growth and Mature
Forests Near Spotted Owl Nests in Western Oregon, Journal of Wildlife Management 55(2): 316–
318.
Examples
str(ex2015)
106 ex2016
ex2016 Bumpus Natural Selection Data
Description
Hermon Bumpus analysed various characteristics of some house sparrows that were found on the
ground after a severe winter storm in 1898. Some of the sparrows survived and some perished. This
data set contains the survival status, age, the length from tip of beak to tip of tail (in mm), the alar
extent (length from tip to tip of the extended wings, in mm), the weight in grams, the length of the
head in mm, the length of the humerus (arm bone, in inches), the length of the femur (thigh bones,
in inches), the length of the tibio–tarsus (leg bone, in inches), the breadth of the skull in inches and
the length of the sternum in inches.
Usage
ex2016
Format
A data frame with 87 observations on the following 11 variables.
Status Survival status, factor with levels "Perished" and "Survived"
AG Age, factor with levels "adult" and "juvenile"
TL total length (in mm)
AE alar extent (in mm)
WT weight (in grams)
BH length of beak and head (in mm)
HL length of humerus (in inches)
FL length of femur (in inches)
TT length of tibio–tarsus (in inches)
SK width of skull (in inches)
KL length of keel of sternum (in inches)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
case0201,ex0221
Examples
str(ex2016)
ex2017 107
ex2017 Catholic stance
Description
The Catholic church has explicitly opposed authoritarian rule in some (but not all) Latin American
countries. Although such action could be explained as a desire to counter repression or to increase
the quality of life of its parishioners, A.J. Gill supplies evidence that the underlying reason may
be competition from evangelical Protestant denominations. He compiled the data given in this data
frame.
Usage
ex2017
Format
A data frame with 12 observations on the following 5 variables.
Stance Catholic church stance, factor with levels "Pro" and "Anti"
Country Latin American country
PQLI Physical Quality of Life Index in the mid-1970s; Average of live expectancy at age 1, infant
mortality and literacy at age 15+.
Repress Average civil rights score for the period of authoritarian rule until 1979
Compete Percentage increase of competitive religious groups during the period 1900–1970
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Gill, A.J. (1994). Rendering unto Caesar? Religious Competition and Catholic Strategy in Latin
America, 1962–1979, American Journal of Political Science 38(2): 403–425.
Examples
str(ex2017)
108 ex2018
ex2018 Fatal Car Accidents Involving Tire Failures on Ford Explorers
Description
This data frame contains data on 1995 and later model compact sports utility vehicles involved in
fatal accidents in the United States between 1995 and 1999, excluding those that were struck by
another car and excluding accidents that, according to police reports, involved alcohol.
Usage
ex2018
Format
A data frame with 2321 observations on the following 4 variables.
Make Type of sports utility vehicle, factor with levels "Other" and "Ford"
Vehicle.age Vehicle age (in years); surrogate for age of tires
Passengers Number of passengers
Cause Cause of fatal accident, factor with levels "Not_Tire" and "Tire"
Details
The Ford Explorer is a popular sports utility vehicle made in the United States and sold throughout
the world. Early in its production concern arose over a potential accident risk associated with tires
of the prescribed size when the vehicle was carrying heavy loads, but the risk was thought to be
acceptable if a low tire pressure was recommended. The problem was apparently exacerbated by
a particular type of Firestone tire that was overly prone to separation, especially in warm tempera-
tures. This type of tire was a common one used on Explorers in model years 1995 and later. By the
end of 1999 more than 30 lawsuits had been filed over accidents that were thought to be associated
with this problem. U.S. federal data on fatal car accidents were analysed at that time, showing that
the odds of a fatal accident being associated with tire failure were three times as great for Explorers
as for other sports utility vehicles.
Additional data from 1999 and additional variables may be used to further explore the odds ratio.
It is of interest to see whether the odds that a fatal accident is tire-related depend on whether the
vehicle is a Ford, after accounting for age of the car and number of passengers. Since the Ford tire
problem may be due to the load carried, there is some interest in seeing whether the odds associated
with a Ford depend on the number of passengers.
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
ex1919
Examples
str(ex2018)
ex2115 109
ex2115 Belief Accessibility
Description
The study the effect of context questions prior to target questions, researchers conducted a poll in-
volving 1,054 subjects selected randomly from the Chicago phone directory. To include possibly
unlisted phones, selected numbers were randomly altered in the last position. This data frame con-
tains the responses to one of the questions asked concerning continuing U.S. aid to the Nicaraguan
Contra rebels. Eight different versions of the interview were given, representing all possible com-
binations of three factors at each of two levels. The experimental factors were Context,Mode and
Level.
Context refers to the type of context questions preceding the question about Nicaraguan aid. Some
subjects received a context question about Vietnam, designed to elicit reticence about having the
U.S. become involved in another foreign war in a third–world country. The other context question
was about Cuba, designed to elicit anti–communist sentiments.
Mode refers to whether the target question immediately followed the context question or whether
there were other questions scattered in between.
Level refers to two versions of the context question. In the "high" level the question was worded
to elicit a higher level of agreement than in the "low" level wording.
Usage
ex2115
Format
A data frame with 8 observations on the following 5 variables.
Context Factor referring to the context of the question preceding the target question about U.S. aid
to the Nicaraguan Contra rebels
Mode Factor with levels "not" and "scattered","scattered" is used if the target question was
not asked directly after the context question
Level Factor with levels "low" and "high", refers to the wording of the question
MNumber of people interviewed
Percent Percentage in favour of Contra aid
Details
Increasingly, politicians look to public opinion surveys to shape their public stances. Does this
represent the ultimate in democracy? Or are seemingly scientific polls being rigged by the manner of
questioning? Psychologists believe that opinions—expressed as answers to questions—are usually
generated at the time the question is asked. Answers are based on a quick sampling of relevant
beliefs held by the subject, rather than a systematic canvas of all such beliefs. Furthermore, this
sampling of beliefs tends to overrepresent whatever beliefs happen to be most accessible at the time
the question is asked. This aspect of delivering opinions can be abused by the pollster. Here, for
example, is one sequence of questions:
(1) “Do you believe the Bill of Rights protects personal freedom?”
110 ex2116
(2) “Are you in favor of a ban on handguns?”
Here is another:
(1) “Do you think something should be done to reduce violent crime?”
(2) “Are you in favor of a ban on handguns?”
The proportion of yes answers to question 2 may be quite different depending on which question 1
is asked first.
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Tourangeau, R., Rasinski, K.A., Bradburn, N. and D’Andrade, R. (1989). Belief Accessibility and
Context Effects in Attitude Measurement, Journal of Experimental Social Psychology 25: 401–421.
Examples
str(ex2115)
ex2116 Aflatoxicol and Liver Tumors in Trout
Description
An experiment at the Marine/Freshwater Biomedical Sciences Center at Oregon State University
investigated the carcinogenic effects of aflatoxicol, a metabolite of Aflatoxin B1, which is a toxic
by-product produced by a mold that infects cottonseed meal, peanuts and grains. Twenty tanks of
rainbow trout embryos were exposed to one of five doses of Aflatoxicol for one hour. The data
represent the numbers of fish in each tank and the numbers of these that had liver tumours after one
year.
Usage
ex2116
Format
A data frame with 20 observations on the following 3 variables.
Dose Dose (in ppm)
Tumor Number of trout with liver tumours
Total Number of trout in tank
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
ex2117 111
Examples
str(ex2116)
ex2117 Effect of Stress During Conception on Odds of a Male Birth
Description
The probability of a male birth in humans is about .51. It has previously been noticed that lower
proportions of male births are observed when offspring is conceived at times of exposure to smog,
floods or earthquakes. Danish researchers hypothesised that sources of stress associated with severe
life events may also have some bearing on the sex ratio. To investigate this theory they obtained the
sexes of all 3,072 children who were born in Denmark between 1 January 1980 and 31 December
1992 to women who experienced the following kind of severe life events in the year of the birth or
the year prior to the birth: death or admission to hospital for cancer or heart attack of their partner or
of their other children. They also obtained sexes on a sample of 20,337 births to mothers who did not
experience these life stress episodes. This data frame contains the data that were collected. Noticed
that for one group the exposure is listed as taking place during the first trimester of pregnancy. The
rationale for this is that the stress associated with the cancer or heart attack of a family member may
well have started before the recorded time of death or hospital admission.
Usage
ex2117
Format
A data frame with 5 observations on the following 4 variables.
Group Indicator for groups to which mothers belong
Time Indicator for time at which severe life event occurred
Number Number of births
PctBoys Percentage of boys born
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Hansen, D., Møller, H. and Olsen, J. (1999). Severe Periconceptional Life Events and the Sex
Ratio in Offspring: Follow Up Study based on Five National Registers, British Medical Journal
319(7209): 548–549.
Examples
str(ex2117)
112 ex2118
ex2118 HIV and Circumcision
Description
Researchers in Kenya identified a cohort of more that 1,000 prostitutes who were known to be a
major reservoir of sexually transmitted diseases in 1985. It was determined that more than 85% of
them were infected with human immunodeficiency virus (HIV) in February, 1986. The researchers
identified men who acquired a sexually-transmitted disease from this group of women after the men
sought treatment at a free clinic. The data frame contains data on the subset of those men who did
not test positive for HIV on their first visit and who agreed to participate in the study. The men are
categorised according to whether they later tested positive for HIV during the study period, whether
they had one or multiple sexual contacts with the prostitutes and whether they were circumcised.
Usage
ex2118
Format
A data frame with 4 observations on the following 5 variables.
Contact Whether men had single or multiple contact with prostitutes
Circumcised Whether the men are circumcised, factor with levels "no" and "yes"
HIV Number of men that tested positive for HIV
Number Number of men
NoHIV Number of men that did not test positive for HIV (should be Number-HIV)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Cameron, D.W., D’Costa, L.J., Maitha, G.M., Cheang, M., Piot, P., Simonsen, J.N., Ronald, A.R.,
Gakinya, M.N., Ndinya-Achola, J.O., Brunham, R.C. and Plummer, F. A. (1989). Female to Male
Transmission of Human Immunodeficiency Virus Type I: Risk Factors for Seroconversion in Men,
The Lancet 334(8660): 403–407.
Examples
str(ex2118)
ex2119 113
ex2119 Meta–Analysis of Breast Cancer and Lactation Studies
Description
This data frame gives the results of 10 separate case–control studies on the association of breast
cancer and whether a woman had breast–fed children.
Usage
ex2119
Format
A data frame with 20 observations on the following 4 variables.
Study Factor indicating the study from which data was taken
Lactate Whether women had breast–fed children (lactated)
Cancer Number of women with breast cancer
NoCancer Number of women without breast cancer
Details
Meta–analysis refers to the analysis of analyses. When the main results of studies can be cast into
2×2 tables of counts, it is natural to combine individual odds ratios with a logistic regression model
that includes a factor to account for different odds from the different studies. In addition, the odds
ratio itself might differ slightly among studies because of different effects on different populations
or different research techniques. One approach for dealing with this is to suppose an underlying
common odds ratio and to model between–study variability as extra–binomial variation.
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Data gathered from various sources by Karolyn Kolassa as part of a Master’s project, Oregon State
University.
Examples
str(ex2119)
114 ex2216
ex22.20 Cancer Death of Atomic Bomb Survivors
Description
The data in this data frame are the number of cancer deaths among survivors of the atomic bombs
dropped on Japan during World War II, categorised by time (years) after the bomb that death oc-
curred and the amount of radiation exposure that the survivors received from the blast (Data from
D.A. Pierce, personal communication.) Also listed in each cell is the person-years at risk, in 100s.
This is the sum total of all years spent by all persons in the category.
Usage
ex22.20
Format
A data frame with 42 observations on the following 4 variables.
Exposure Estimated exposure to radiation (in rads)
Years Years after exposure, factor with 7 levels
Deaths Number of cancer deaths
Risk Person-years at risk (in 100s)
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
str(ex22.20)
ex2216 Murder–Suicides by Deliberate Plane Crash
Description
Some sociologist suspect that highly publicised suicides may trigger additional suicides. In one
investigation of this hypothesis, D.P. Phillips collected information about 17 airplane crashes that
were known (because of notes left behind) to be murder–suicides. For each of these crashes, Phillips
reported an index of the news coverage (circulation of nine newspapers devoting space to the crash
multiplied by length of coverage) and the number of multiple-fatality plane crashes during the week
following the publicised crash. This data frame contains the collected data.
Usage
ex2216
ex2222 115
Format
A data frame with 17 observations on the following 2 variables.
Index Index for the amount of newspaper coverage given the murder–suicide
Crashes Multiple-fatality crashes in the week following a murder–suicide by plane crash
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Phillips, D.P. (1978). Airplane Accident Fatalities Increase Just After Newspaper Stories About
Murder and Suicide, Science 201: 748–750.
Examples
str(ex2216)
ex2222 Emulating Jane Austen’s Writing Style
Description
When she died in 1817, the English novelist Jane Austen had not yet finished the novel Sanditon,
but she did leave notes on how she intended to conclude the book. The novel was completed by
a ghost writer, who attempted to emulate Austen’s style. In 1978, a researcher reported counts of
some words found in chapters of books written by Austen and in chapters written by the emulator.
These data are given in this data frame.
Usage
ex2222
Format
A data frame with 24 observations on the following 3 variables.
Count Number of occurrences of a word in various chapters of books written by Jane Austen and
the ghost writer
Book Title of books used
Word Words used
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
116 ex2223
References
Morton, A.Q. (1978). Literary Detection: How to Prove Authorship and Fraud in Literature and
Documents, Charles Scribner’s Sons, New York.
Examples
str(ex2222)
ex2223 Space Shuttle O-Ring Failures
Description
On January 27, 1986, the night before the space shuttle Challenger exploded, an engineer rec-
ommended to the National Aeronautics and Space Administration (NASA) that the shuttle not be
launched in the cold weather. The forecasted temperature for the Challenger launch was 31 degrees
Fahrenheit—the coldest launch ever. After an intense 3-hour telephone conference, officials de-
cided to proceed with the launch. This data frame contains the launch temperatures and the number
of O-ring problems in 24 shuttle launches prior to the Challenger.
Usage
ex2223
Format
A data frame with 24 observations on the following 2 variables.
Temp Launch temperatures (in degrees Fahrenheit)
Incident Numbers of O-ring incidents
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
See Also
case0401,ex2011
Examples
str(ex2223)
ex2224 117
ex2224 Valve Failure in Nuclear Reactors
Description
This data frame contains data on characteristics and numbers of failures observed in valve types
from one pressurised water reactor.
Usage
ex2224
Format
A data frame with 90 observations on the following 7 variables.
System System, factor with 5 levels
Operator Operator type, factor with 4 levels
Valve Valve type, factor with 6 levels
Size Head size, factor with 3 levels (less than 2 inches, 2–10 inches and 10–30 inches)
Mode Operation mode, factor with 2 levels
Failures Number of failures observed
Time Lengths of observation time
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Moore, L.M. and Beckman, R.J. (1988). Appropriate One-Sided Tolerance Bounds on the Number
of Failures using Poisson Regression, Technometrics 30: 283–290.
Examples
str(ex2224)
118 ex2414
ex2225 Body Size and Reproductive Success in a Population of Male Bullfrogs
Description
As an example of field observation in evidence of theories of sexual selection, S.J. Arnold and M.J.
Wade presented the following data set on size and number of mates observed in 38 bullfrogs.
Usage
ex2225
Format
A data frame with 38 observations on the following 2 variables.
Bodysize Body size (in mm)
Mates Number of mates
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Arnold, S.J. and Wade, M.J. (1984). On the Measurement of Natural and Sexual Selection: Aplica-
tions, Evolution 38: 720–734.
Examples
str(ex2225)
ex2414 Amphibian Crisis and UV-B
Description
Data frame contains the percentage of unsuccessful hatching from enclosures containing 150 eggs
each in a study to investigate whether UV-B is responsible for low hatch rates.
Usage
ex2414
Sleuth2Manual 119
Format
A data frame with 71 observations on the following 4 variables.
Percent percentage of frog eggs failing to hatch
Treat factor variable with levels "NoFilter","UV-BTransmitting" and "UV-BBlocking"
Location factor variable with levels "ThreeCreeks","SparksLake","SmallLake" and "LostLake"
Phtolyas Photolyase activity
Source
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
References
Blaustein, A.R., Hoffman, P.D., Hokit, D.G., Kiesecker, J.M., Walls, S.C. and Hays, J.B. (1994).
UV Repair and Resistance to Solar UV-B in Amphibian Eggs: A Link to Population Declines?
Proceedings of the National Academy of Science, USA 91: 1791–1795.
Examples
str(ex2414)
Sleuth2Manual Manual of the R Sleuth2 package
Description
If the option “pdfviewer” is set, this command will display the PDF version of the help pages.
Usage
Sleuth2Manual()
Author(s)
Berwin A Turlach <Berwin.Turlach@gmail.com>
References
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data
Analysis (2nd ed), Duxbury.
Examples
## Not run: Sleuth2Manual()
Index
∗Topic datasets
case0101,5
case0102,5
case0201,6
case0202,7
case0301,8
case0302,9
case0401,9
case0402,10
case0501,11
case0502,12
case0601,13
case0602,14
case0701,15
case0702,16
case0801,17
case0802,17
case0901,18
case0902,19
case1001,19
case1002,20
case1101,21
case1102,22
case1201,23
case1202,24
case1301,25
case1302,26
case1401,27
case1402,28
case1501,29
case1502,30
case1601,31
case1602,32
case1701,33
case1702,34
case1902,35
case2001,37
case2002,38
case2101,39
case2102,40
case2201,41
case2202,41
ex0112,42
ex0116,43
ex0211,44
ex0221,44
ex0222,45
ex0223,46
ex0321,46
ex0323,47
ex0327,48
ex0328,49
ex0331,49
ex0332,50
ex0333,51
ex0428,51
ex0429,52
ex0430,53
ex0431,53
ex0432,54
ex0518,55
ex0523,55
ex0524,56
ex0621,57
ex0622,57
ex0723,59
ex0724,60
ex0726,61
ex0727,61
ex0728,62
ex0729,63
ex0730,63
ex0816,64
ex0817,65
ex0818,66
ex0820,66
ex0822,67
ex0823,68
ex0824,69
ex0825,69
ex0914,70
ex0915,71
ex0918,71
ex0920,72
ex1014,73
ex1026,74
120
INDEX 121
ex1027,74
ex1028,75
ex1029,76
ex1115,77
ex1120,77
ex1122,78
ex1123,79
ex1124,80
ex1217,80
ex1220,82
ex1221,83
ex1222,84
ex1317,85
ex1319,85
ex1320,86
ex1414,87
ex1415,88
ex1417,89
ex1509,89
ex1512,90
ex1513,91
ex1514,91
ex1515,92
ex1605,93
ex1611,94
ex1612,94
ex1613,95
ex1614,96
ex1615,96
ex1708,97
ex1713,98
ex1714,99
ex1914,100
ex1916,100
ex1917,101
ex1918,102
ex1919,103
ex2011,103
ex2012,104
ex2015,105
ex2016,106
ex2017,107
ex2018,108
ex2115,109
ex2116,110
ex2117,111
ex2118,112
ex2119,113
ex22.20,114
ex2216,114
ex2222,115
ex2223,116
ex2224,117
ex2225,118
ex2414,118
∗Topic documentation
Sleuth2Manual,119
∗Topic package
Sleuth2-package,4
case0101,5
case0102,5,24
case0201,6,45,106
case0202,7
case0301,8
case0302,9
case0401,9,104,116
case0402,10
case0501,11
case0502,12
case0601,13
case0602,14
case0701,15,61,62
case0702,16,64,65
case0801,17
case0802,17
case0901,18
case0902,19,19,51
case1001,19
case1002,20
case1101,21
case1102,22
case1201,23
case1202,6,24
case1301,25
case1302,26
case1401,27
case1402,28
case1501,29
case1502,30
case1601,31
case1602,32
case1701,33
case1702,34
case1902,35
case2001,37,102
case2002,38
case2101,39
case2102,40
case2201,41
case2202,41
ex0112,42
ex0116,43
ex0211,44
122 INDEX
ex0221,7,44,106
ex0222,45
ex0223,46
ex0321,46
ex0323,47
ex0327,48
ex0328,49
ex0331,49
ex0332,50
ex0333,51
ex0428,51
ex0429,52
ex0430,53
ex0431,53
ex0432,54
ex0518,55
ex0523,55,78
ex0524,56
ex0621,57
ex0622,57
ex0723,59
ex0724,60
ex0726,61
ex0727,16,61
ex0728,62
ex0729,63
ex0730,63
ex0816,16,64
ex0817,65
ex0818,66
ex0820,66,77
ex0822,67
ex0823,68
ex0824,69
ex0825,69,84
ex0914,70
ex0915,71
ex0918,71
ex0920,72
ex1014,73
ex1026,74
ex1027,74
ex1028,75
ex1029,76
ex1115,67,77
ex1120,56,77
ex1122,78
ex1123,79,80,81
ex1124,80
ex1217,79,80
ex1220,82
ex1221,83
ex1222,70,84
ex1317,85
ex1319,85,93
ex1320,86
ex1414,87,88
ex1415,87,88
ex1417,89
ex1509,89
ex1512,90
ex1513,91
ex1514,91
ex1515,92
ex1605,86,93
ex1611,94
ex1612,94
ex1613,95
ex1614,96
ex1615,96
ex1708,97
ex1713,98
ex1714,99
ex1914,100
ex1916,100
ex1917,101
ex1918,37,102
ex1919,103,108
ex2011,10,103,116
ex2012,104
ex2015,105
ex2016,7,45,106
ex2017,107
ex2018,103,108
ex2115,109
ex2116,110
ex2117,111
ex2118,112
ex2119,113
ex22.20,114
ex2216,114
ex2222,115
ex2223,10,104,116
ex2224,117
ex2225,118
ex2414,118
Sleuth2 (Sleuth2-package),4
Sleuth2-package,4
Sleuth2Manual,119

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