PrefaceAcknowledgmentsForewardChapter 1: Making the Right Comparison: Understanding the Rules and Limitations of Quantitative ReasoningPositive and Normative StatementsDeduction and InductionDeduction and InductionUsing Deduction and Induction TogetherCause and AssociationLinking Deduction with Induction - Measurement ValidityA Note of Caution on MeasurementLinking Deduction with Induction - Measurement ReliabilityExercisesChapter 2: Making the Right Comparison: Observations, Variable Types, Data Displays, and Data ConversionsData Sets and Variable TypesVariable Types and Data DisplaysChoice of Divisor in Creating RatiosOther Types of Data Conversions: Adjusting for InflationOther Types of Data Conversions: Adjusting for SeasonalityOther Types of Data Conversions: Adjusting for NoiseExercisesChapter 3: Using Stata and Excel to Create Line, Bar, and Scatter DiagramsUsing StataUploading Data into StataExecuting Basic Commands in StataSaving Your WorkUsing ExcelUploading Data into ExcelExecuting Basic Commands in ExcelSaving Your WorkExercisesChapter 4: Summarizing Variables using Measures of Central Tendency and DispersionMeasures of Central Tendency - The MeanMeasures of Central Tendency - The MedianMeasures of Central Tendency - The ModeMeasures of Dispersion - The RangeMeasures of Dispersion - Mean Absolute DeviationMeasures of Dispersion - Variance and Standard DeviationPopulations and SamplesAppendix: Measures of Central Tendency and Dispersion using Statistical SoftwareMeasures of Central Tendency and Dispersion in StataHistograms in StataMeasures of Central Tendency and Dispersion in ExcelHistograms in ExcelExercisesChapter 5: Research Design and Statistical FallaciesRandom Assignment and Wellness ProgramsBroader Lessons from Comparing Studies on the Effectiveness of Wellness ProgramsInferring Cause When RCTs Are Not PossibleWrongly Inferring Association: Regression Fallacy and MaturationWrongly Inferring Association: Ecological and Reductionist FallaciesWrongly Inferring Association: Simpson''s ParadoxWrongly Inferring Association: Cherry PickingWrongly Inferring Cause: Selection Bias and Sample MortalityWrongly Inferring Cause: Bidirectional CausalityExercisesChapter 6: Constructing Informative Comparisons and Inferring CauseJohn Snow''s EvidenceJohn Snow, Cholera, and General Rules for Quantitative ComparisonsDescriptive, Correlational, and Causal ResearchThe Difficulty of Establishing Cause Varies with ContextSorting Data and Making Comparisons to Produce Evidence on CauseData Sorting and Cause: An ExampleDifference-in-Differences AnalysisDifference-in-Differences: An ExampleDiscontinuity AnalysisDiscontinuity Analysis: An ExampleExercisesChapter 7: Sampling Distributions and Statistical InferenceBasic ProbabilityRandom Variables and Their Probability DistributionsDiscrete Probability FunctionsProbability Density FunctionsThe Uniform Probability DistributionThe Normal Probability DistributionThe Sampling Distribution and the Central Limit TheoremConfidence IntervalsConfidence Intervals for Means Using the z Distribution (s Known)Confidence Intervals for Proportions Using the z DistributionConfidence Intervals for Means Using the t Distribution (s Unknown)Choosing the Right Procedure to Calculate a Confidence IntervalExercisesChapter 8: One-Sample Hypothesis TestsThe Basic Structure of Hypothesis TestsThe Null and the Alternative HypothesesOne-Tailed and Two-Tailed Hypothesis TestsType I and Type II ErrorsOne- and Two-Sample Hypothesis TestsSampling Distributions and the Structure of One-Sample Hypothesis TestsUnderstanding Test Statistics for One-Sample Hypothesis TestsExecuting One-Sample Hypothesis Tests for a Population Mean Using the z DistributionExecuting One-Sample Hypothesis Tests for a Population Proportion Using the z DistributionSummarizing the Steps for One-Sample Hypothesis TestsHypothesis Tests and Confidence IntervalsAppendix: Confidence Intervals and Hypothesis Tests Using Statistical SoftwareConfidence Intervals and Hypothesis Tests in Stata Using Univariate MeasuresConfidence Intervals and Hypothesis Tests in Stata Using Sample ObservationsConfidence Intervals and Hypothesis Tests in Excel Using Sample ObservationsExercisesChapter 9: Two-Sample Hypothesis Tests of MeansTwo-Sample Hypothesis Tests and CauseUndefined Populations and External ValidityDependent and Independent SamplesOne-Sample Hypothesis Tests and Two-Sample Hypothesis TestsTwo-Sample Hypothesis Tests of Means: Independent SamplesTesting Population VariancesTwo-Sample Hypothesis Tests of Proportions in Stata Using Sample ObservationsExecuting Two-Sample Hypothesis Tests on Means: MurdersSummarizing the Two-Sample Hypothesis Tests for Differences in MeansAppendix: Two-Sample Hypothesis Tests of Means Using Statistical SoftwareTwo-Sample Hypothesis Tests of Means in Stata Using Univariate MeasuresTwo-Sample Hypothesis Tests of Means in Stata Using Sample ObservationsTwo-Sample Hypothesis Tests of Means in Excel Using Sample ObservationsExercisesChapter 10: Two-Sample Hypothesis Tests of ProportionsTwo-Sample Hypothesis Test for Proportions: Independent SamplesTwo-Sample Hypothesis Test for Proportions: Dependent SamplesExecuting Two-Sample Hypothesis Tests on Proportions: Leg Restraints and LeadershipSummarizing the Two-Sample Hypothesis Tests for Differences in ProportionsAppendix: Two-Sample Hypothesis Tests of Proportions Using Statistical SoftwareTwo-Sample Hypothesis Tests of Proportions in Stata Using Univariate MeasuresTwo-Sample Hypothesis Tests of Proportions in Stata Using Sample ObservationsTwo-Sample Hypothesis Tests of Proportions in Excel Using Sample ObservationsExercisesChapter 11: Correlation and Simple Linear RegressionCorrelationCalculating the Correlation Coefficient and Testing the Hypothesis ? = 0Simple Linear RegressionSimple Linear Regression as Estimating Relationships Using (x, y) CoordinatesCalculating Coefficients in a Simple Linear RegressionTesting Coefficients of a Simple Linear RegressionCalculating R2Appendix: Correlation and Simple Linear Regression Using Statistical SoftwareCorrelation in StataSimple Linear Regression in StataCorrelation in ExcelSimple Linear Regression in ExcelExercisesChapter 12: Simple Linear Regression: Assumptions and ExtensionsAssumptions of Simple Linear RegressionNonlinear Relationships and Log Transformation in Simple Linear RegressionDichotomous Independent Variables in Simple Linear RegressionDetecting and Correcting Serial AutocorrelationDetecting and Correcting HeteroskedasticityTransforming Variables to Support Causal Claims: Time Lags and ChangesAppendix: Simple Linear Regression Procedures Using Statistical SoftwareExecuting Log-Transform Simple Linear Regression in StataDetecting and Correcting Serial Autocorrelation in StataDetecting and Correcting Heteroskedasticity in StataUsing Stata to Transform Variables and Generate Evidence on CauseExecuting Log-Transform Simple Linear Regression in ExcelDetecting Serial Correlation in ExcelDetecting Heteroskedasticity in ExcelUsing Excel to Transform Variables and Generate Evidence on CauseExercisesGlossary.