Statistical methods for the social sciences

564 Pages·14.761 MB·English

by  Agresti, Alan

GLOBAL
EDITION
Statistical Methods
for the Social Sciences
FIFTH EDITION
ALAN AGRESTI
S M
TATISTICAL ETHODS FOR
S S
THE OCIAL CIENCES
Fifth Edition
Global Edition
Alan Agresti
University of Florida
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TO MY PARENTS
LOUIS J. AGRESTI AND MARJORIE H. AGRESTI
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Contents
Preface 9 4.4 SamplingDistributionsDescribeHow
StatisticsVary 92
Acknowledgments 11 4.5 SamplingDistributionsofSampleMeans 97
4.6 Review:Population,SampleData,and
1
Introduction 13 SamplingDistributions 103
4.7 ChapterSummary 106
1.1 IntroductiontoStatisticalMethodology 13
5
1.2 DescriptiveStatisticsandInferential Statistical Inference:
Statistics 16
Estimation 115
1.3 TheRoleofComputersandSoftwarein
Statistics 18 5.1 PointandIntervalEstimation 115
1.4 ChapterSummary 20 5.2 ConfidenceIntervalforaProportion 118
2 5.3 ConfidenceIntervalforaMean 125
Sampling and Measurement 23
5.4 ChoiceofSampleSize 132
2.1 VariablesandTheirMeasurement 23 5.5 EstimationMethods:MaximumLikelihood
andtheBootstrap∗ 138
2.2 Randomization 26
5.6 ChapterSummary 142
2.3 SamplingVariabilityandPotentialBias 29
2.4 OtherProbabilitySamplingMethods∗ 33 6
Statistical Inference:
2.5 ChapterSummary 35 Significance Tests 151
3
Descriptive Statistics 41 6.1 TheFivePartsofaSignificanceTest 152
6.2 SignificanceTestforaMean 155
3.1 DescribingDatawithTablesandGraphs 41
6.3 SignificanceTestforaProportion 164
3.2 DescribingtheCenteroftheData 47
6.4 DecisionsandTypesofErrorsinTests 167
3.3 DescribingVariabilityoftheData 53
6.5 LimitationsofSignificanceTests 171
3.4 MeasuresofPosition 58
6.6 FindingP(TypeIIError)∗ 175
3.5 BivariateDescriptiveStatistics 63
6.7 Small-SampleTestforaProportion—the
3.6 SampleStatisticsandPopulation BinomialDistribution∗ 177
Parameters 67
6.8 ChapterSummary 181
3.7 ChapterSummary 67
7
Comparison of Two Groups 191
4
Probability Distributions 79
7.1 PreliminariesforComparingGroups 191
4.1 IntroductiontoProbability 79
7.2 CategoricalData:ComparingTwo
4.2 ProbabilityDistributionsforDiscreteand Proportions 194
ContinuousVariables 81
7.3 QuantitativeData:Comparing
4.3 TheNormalProbabilityDistribution 84 TwoMeans 199
5
6 Contents
7.4 ComparingMeanswithDependent 11
Multiple Regression
Samples 202
and Correlation 319
7.5 OtherMethodsforComparingMeans∗ 205
7.6 OtherMethodsforComparing 11.1 TheMultipleRegressionModel 319
Proportions∗ 210
11.2 MultipleCorrelationandR2 328
7.7 NonparametricStatisticsfor
ComparingGroups∗ 213 11.3 InferencesforMultipleRegression
Coefficients 332
7.8 ChapterSummary 216
11.4 ModelingInteractionEffects 337
8 11.5 ComparingRegressionModels 341
Analyzing Association between
Categorical Variables 227 11.6 PartialCorrelation∗ 343
11.7 StandardizedRegression
8.1 ContingencyTables 227 Coefficients∗ 346
8.2 Chi-SquaredTestofIndependence 230 11.8 ChapterSummary 349
8.3 Residuals:DetectingthePatternof
Association 237 12
Regression with Categorical
8.4 MeasuringAssociationinContingency
Predictors: Analysis of
Tables 239
Variance Methods 363
8.5 AssociationBetweenOrdinalVariables∗ 245
8.6 ChapterSummary 250 12.1 RegressionModelingwithDummyVariables
forCategories 363
9
Linear Regression 12.2 MultipleComparisonsofMeans 367
and Correlation 259 12.3 ComparingSeveralMeans:Analysisof
Variance 370
9.1 LinearRelationships 259
12.4 Two-WayANOVAandRegression
9.2 LeastSquaresPredictionEquation 262 Modeling 374
9.3 TheLinearRegressionModel 268 12.5 Repeated-MeasuresAnalysisof
Variance∗ 381
9.4 MeasuringLinearAssociation:
TheCorrelation 271 12.6 Two-WayANOVAwithRepeatedMeasures
onaFactor∗ 385
9.5 InferencesfortheSlopeand
Correlation 278 12.7 ChapterSummary 390
9.6 ModelAssumptionsandViolations 284
13
9.7 ChapterSummary 289 Multiple Regression with
Quantitative and Categorical
10
Introduction to Multivariate Predictors 399
Relationships 299
13.1 ModelswithQuantitativeandCategorical
10.1 AssociationandCausality 299 ExplanatoryVariables 399
10.2 ControllingforOtherVariables 302 13.2 InferenceforRegressionwith
QuantitativeandCategorical
10.3 TypesofMultivariateRelationships 306
Predictors 406
10.4 InferentialIssuesinStatisticalControl 311
13.3 CaseStudies:UsingMultipleRegression
10.5 ChapterSummary 313 inResearch 409
Contents 7
13.4 AdjustedMeans∗ 413 15.3 InferenceforLogisticRegression
13.5 TheLinearMixedModel∗ 418 Models 482
15.4 LogisticRegressionModelsforOrdinal
13.6 ChapterSummary 423
Variables∗ 484
14 15.5 LogisticModelsforNominal
Model Building with Multiple Responses∗ 489
Regression 431
15.6 LoglinearModelsforCategorical
Variables∗ 492
14.1 ModelSelectionProcedures 431
15.7 ModelGoodness-of-FitTestsfor
14.2 RegressionDiagnostics 438 ContingencyTables∗ 496
14.3 EffectsofMulticollinearity 445
15.8 ChapterSummary 500
14.4 GeneralizedLinearModels 447
14.5 NonlinearRelationships:Polynomial Appendix: R, Stata, SPSS, and SAS
Regression 451 for Statistical Analyses
509
14.6 ExponentialRegressionandLog
Transforms∗ 456
Bibliography
545
14.7 RobustVariancesandNonparametric
Regression∗ 460
Credits
14.8 ChapterSummary 462 549
15
Logistic Regression: Modeling Index 551
Categorical Responses 471
15.1 LogisticRegression 471
15.2 MultipleLogisticRegression 477
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Preface
When Barbara Finlay and I undertook the first edition of this book nearly four
decadesago,ourgoalwastointroducestatisticalmethodsinastylethatemphasized
their concepts and their application to the social sciences rather than the mathe-
maticsandcomputationaldetailsbehindthem.Wedidthisbyfocusingonhowthe
methodsareusedandinterpretedratherthantheirtheoreticalderivations.
Thiseditionof thebook continues theemphasis onconcepts andapplications,
usingexamplesandexerciseswithavarietyof“realdata.”Thiseditionincreasesits
illustrationsofstatisticalsoftwareforcomputations,andtakesadvantageoftheout-
standingappletsnowavailableontheInternetforexplainingkeyconceptssuchas
samplingdistributionsandforconductingbasicdataanalyses.Icontinuetodownplay
mathematics,inparticularprobability,whichisalltoooftenastumblingblockforstu-
dents.Ontheotherhand,thetextisnotacookbook.Relianceonanoverlysimplistic
recipe-basedapproachtostatisticsisnottheroutetogoodstatisticalpractice.
Changes in the Fifth Edition
UsersofearliereditionswillnoticethatthebooknolongerlistsBarbaraFinlayas
a co-author. I am grateful to Barbara Finlay for her contributions to the first two
editions of this text. Combining her sociology background with my statistics back-
ground,sheverymuchhelpedmedevelopabookthatisnotonlystatisticallysound
butalsorelevanttothesocialsciences.
Sincethefirstedition,theincreaseincomputerpowercoupledwiththecontin-
uedimprovementandaccessibilityofstatisticalsoftwarehashadamajorimpacton
thewaysocialscientistsanalyzedata.Becauseofthis,thisbookdoesnotcoverthe
traditionalshortcuthand-computationalformulasandapproximations.Thepresen-
tationofcomputationallycomplexmethods,suchasregression,emphasizesinterpre-
tationofsoftwareoutputratherthantheformulasforperformingtheanalysis.The
textcontainsnumeroussamplesoftwareoutputs,bothinchaptertextandinhome-
workexercises.Intheappendixonusingstatisticalsoftware,thiseditionaddsRand
StatatothematerialonSPSSandSAS.
Exposuretorealisticbutsimpleexamplesandtonumeroushomeworkexercises
is vital to student learning. This edition has updated data in most of the exercises
andreplacedsomeexerciseswithnewones.Eachchapter’shomeworksetisdivided
intotwoparts,straightforwardexercisesonthetextmaterialinPracticingtheBasics
andexercisesdealingwithopen-endeddataanalyses,understandingofconcepts,and
advancedmaterialinConceptsandApplications.Thedatasetsintheexamplesand
exercisesareavailableatwww.pearsonglobaleditions.com/Agresti.
Thiseditioncontainssomechangesandadditionsincontent,directedtowarda
moremodernapproach.Themainchangesareasfollows:
• Thetexthasgreaterintegrationofstatisticalsoftware.Softwareoutputshown
nowusesRandStatainsteadofonlySASandSPSS,althoughmuchoutputhas
agenericappearance.Thetextappendixprovidesinstructionsaboutbasicuse
ofthesesoftwarepackages.
• New examples and exercises in Chapters 4–6 ask students to use applets to
help learn the fundamental concepts of sampling distributions, confidence
9