book

Statistics in a Nutshell, 2nd Edition

by Sarah Boslaugh

November 2012

Beginner

594 pages

19h 6m

English

O'Reilly Media, Inc.

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OK, Just What Is Statistics?The Focus of This BookStatistics in the Age of InformationOrganization of This BookConventions Used in This BookUsing Code ExamplesSafari® Books OnlineHow to Contact UsAcknowledgments
MeasurementLevels of MeasurementNominal DataOrdinal DataInterval DataRatio DataContinuous and Discrete DataOperationalizationProxy MeasurementTrue and Error ScoresRandom and Systematic ErrorReliability and ValidityReliabilityValidityTriangulationMeasurement BiasBias in Sample Selection and RetentionInformation BiasExercises
About FormulasBasic DefinitionsTrialsSample SpaceEventsUnionIntersectionComplementMutual ExclusivityIndependencePermutationsCombinationsDefining ProbabilityExpressing the Probability of an EventConditional ProbabilitiesCalculating the Probability of Multiple EventsUnion of mutually exclusive eventsUnion of events that are not mutually exclusiveIntersection of independent eventsIntersection of nonindependent eventsBayes’ TheoremEnough Exposition, Let’s Do Some Statistics!Dice, Coins, and Playing CardsExercisesClosing Note: The Connection between Statistics and Gambling
Probability DistributionsThe Normal DistributionThe Binomial DistributionIndependent and Dependent VariablesPopulations and SamplesNonprobability SamplingProbability SamplingThe Central Limit TheoremHypothesis TestingConfidence Intervalsp-valuesThe Z-StatisticData TransformationsExercises
Populations and SamplesMeasures of Central TendencyThe MeanThe MedianThe ModeComparing the Mean, Median, and ModeMeasures of DispersionThe Range and Interquartile RangeThe Variance and Standard DeviationOutliersGraphic MethodsFrequency TablesBar ChartsPie ChartsPareto ChartsThe Stem-and-Leaf PlotThe BoxplotThe HistogramBivariate ChartsScatterplotsLine GraphsExercises
The R×C TableMeasures of AgreementThe Chi-Square DistributionThe Chi-Square TestFisher’s Exact TestMcNemar’s Test for Matched PairsProportions: The Large Sample CaseCorrelation Statistics for Categorical DataBinary VariablesThe Point-Biserial Correlation CoefficientOrdinal VariablesThe Likert and Semantic Differential ScalesExercises
The t DistributionThe One-Sample t-TestConfidence Interval for the One-Sample t-TestThe Independent Samples t-TestConfidence Interval for the Independent Samples t-TestRepeated Measures t-TestConfidence Interval for the Repeated Measures t-TestUnequal Variance t-TestExercises
AssociationScatterplotsRelationships Between Continuous VariablesThe Pearson Correlation CoefficientTesting Statistical Significance for the Pearson CorrelationThe Coefficient of DeterminationExercises

The General Linear ModelLinear RegressionAssumptionsAnalysis of Variance (ANOVA)One-Way ANOVAPost Hoc TestsCalculating Simple Regression by HandExercisesRegressionANOVA
Factorial ANOVAInteractionTwo-Way ANOVAThree-Way ANOVAANCOVAExercises
Multiple Regression ModelsDummy VariablesMethods for Building Regression ModelsForward entryBackward removalExercisesExample 1Example 2
Logistic RegressionConverting Logits to ProbabilitiesMultinomial Logistic RegressionPolynomial RegressionOverfittingExercises
Factor AnalysisCluster AnalysisDiscriminant Function AnalysisExercises
Between-Subjects DesignsThe Wilcoxon Rank Sum TestThe Sign TestThe Median TestKruskal-Wallis H TestWithin-Subjects DesignsWilcoxon Signed Ranks TestFriedman TestExercises
Index NumbersTime SeriesDecision AnalysisMinimax, Maximax, and MaximinDecision Making under RiskDecision TreesQuality ImprovementRun Charts and Control ChartsExercises
Measures of Disease FrequencyRatio, Proportion, and RatePrevalence and IncidenceCrude, Category-Specific, and Standardized RatesThe Risk RatioAttributable Risk, Attributable Risk Percentage, and Number Needed to TreatThe Odds RatioConfounding, Stratified Analysis, and the Mantel-Haenszel Common Odds RatioPower AnalysisSample Size CalculationsConfidence Interval for a ProportionPower for the Test of the Difference between Two Sample Means (Independent Samples t-Test)Exercises
PercentilesStandardized ScoresTest ConstructionClassical Test Theory: The True Score ModelReliability of a Composite TestMeasures of Internal ConsistencySplit-Half MethodsCoefficient AlphaItem AnalysisItem Response TheoryExercises
An Approach, Not a Set of RecipesThe Chain of CommandCodebooksThe Rectangular Data FileSpreadsheets and Relational DatabasesInspecting a New Data FileString and Numeric DataMissing Data
Basic VocabularyObservational StudiesQuasi-Experimental StudiesExperimental StudiesIngredients of a Good DesignGathering Experimental DataIdentifying Experimental UnitsIdentifying Treatments and ControlsSpecifying Treatment LevelsSpecifying Response VariablesBlindingRetrospective AdjustmentBlocking and the Latin SquareExample Experimental Design
General NotesWriting for a Professional JournalWriting the ArticleThe Peer Review ProcessWriting for the General PublicWriting for Your Workplace
Evaluating the Whole ArticleThe Misuse of StatisticsCommon ProblemsQuick ChecklistIssues in Research DesignVariationPopulationSamplingControlsThe Power of CoincidenceDescriptive StatisticsMeasures of Central TendencyStandard Error and Confidence IntervalsGraphical Presentation of DataExtrapolation and TrendsInferential StatisticsAssumptions of Statistical Testst-testsANOVALinear regression
Laws of ArithmeticOrder of OperationsProperties of Real NumbersExponents and RootsProperties of RootsSolving EquationsSystems of EquationsGraphing EquationsLinear InequalitiesFractionsFactorials, Permutations, and CombinationsExercisesLaws of Arithmetic and Real NumbersExponents, Roots, and LogarithmsNatural LogarithmsSolving Equations for xSystems of Linear EquationsLinear Equations and Cartesian CoordinatesLinear EqualitiesFractions, Decimals, and PercentsFactorials, Permutations, and CombinationsAnswersLaws of Arithmetic and Real NumbersExponents, Roots, and LogarithmsNatural LogarithmsSolving Equations for xSolving Systems of Linear EquationsLinear Equations and Cartesian CoordinatesLinear EqualitiesFractions, Decimals, and PercentsFactorials, Permutations, and Combinations
MinitabSPSSSASRMicrosoft Excel
Preface and General SourcesChapter 1Chapter 2Chapter 3Chapter 4Chapter 5Chapter 6Chapter 7Chapter 8Chapter 9Chapter 10Chapter 11Chapter 12Chapter 13Chapter 14Chapter 15Chapter 16Chapter 17Chapter 18Chapter 19Chapter 20
The Standard Normal DistributionThe t-DistributionThe Binomial DistributionThe Chi-Square Distribution
General ResourcesGlossariesProbability TablesOnline CalculatorsOnline Textbooks

Content preview from Statistics in a Nutshell, 2nd Edition

About the Author

Sarah Boslaugh holds a PhD in Research and Evaluation from the City University of New York and have been working as a statistical analyst for 15 years, in a variety of professional settings, including the New York City Board of Education, the Institutional Research Office of the City University of New York, Montefiore Medical Center, the Virginia Department of Social Services, Magellan Health Services, Washington University School of Medicine, and BJC HealthCare. She has taught statistics in several different contexts and currently teaches Intermediate Statistics at Washington University Medical School. She has published two previous books: An Intermediate Guide to SPSS Programming: Using Syntax for Data Management (SAGE Publications, 2004) and Secondary Data Sources for Public Health (forthcoming from Cambridge U. Press, 2007) and am currently editing the Encyclopedia of Epidemiology for SAGE Publications (forthcoming, 2007).