Chapter 1: Introduction to Statistical ThinkingSome Definitions and Basic IdeasMath Phobia, Panic, and Terror in Social StatisticsThe Practical Value of Social Statistics and Statistical ReasoningTypes of Statistical MethodsPedagogical (Teaching) ApproachesChapter 2: Garbage In, Garbage Out (GIGO)Measurement InvaliditySampling ProblemsFaulty Causal InferencesPolitical InfluencesHuman FallibilityChapter 3: Issues in Data PreparationWhy Is Data Preparation Important?Operationalization and MeasurementNominal Measurement of Qualitative Variables: Measurement of Quantitative Variables: Issues in Levels of Measurement: Coding and Inputting Statistical DataAvailable Computer Software for Basic Data AnalysisChapter 4: Displaying Data in Tables and Graphic FormsThe Importance of Data Tables and GraphsTypes of Tabular and Visual PresentationsTables and Graphs for Qualitative Variables: Tables and Graphs for Quantitative: Variables: Ratios and Rates: Maps of Qualitative and Quantitative: Variables: Hazards and Distortions in Visual Displays and Collapsing CategoriesChapter 5: Modes, Medians, Means, and MoreModes and Modal CategoriesThe Median and Other Measures of LocationThe Mean and Its MeaningWeighted Means: Strengths and Limitations of Mean Ratings: Choice of Measure of Central Tendency and PositionChapter 6: Measures of Variation and DispersionThe Range of ScoresThe Variance and Standard DeviationVariances and Standard Deviations for Binary Variables: Population Versus Sample Variances and Standard DeviationsChapter 7: The Normal Curve and Sampling DistributionsThe Normal CurveZ-Scores as Standard ScoresReading a Normal Curve TableOther Sampling DistributionsBinomial Distribution: t-Distribution: Chi-Square Distribution: F-Distributions: Chapter 8: Parameter Estimation and Confidence IntervalsSampling Distributions and the Logic of Parameter EstimationInferences from Sampling Distributions to One Real SampleConfidence Intervals: Large Samples, ? KnownConfidence Intervals for Population Means: Confidence Intervals for Population Proportions: Confidence Intervals: Small Samples and Unknown ?Properties of the t-Distribution: Confidence Intervals for Population Means for Unknown ?: Confidence Intervals for Population Proportions for Unknown ?: Chapter 9: Introduction to Hypothesis TestingConfidence Intervals Versus Hypothesis TestingBasic Terminology and SymbolsTypes of Hypotheses: Zone of Rejection and Critical Values: Significance Levels and Errors in Decision Making: Chapter 10: Hypothesis Testing for Means and ProportionsTypes of Hypothesis TestingOne-Sample Tests of the Population Mean: One-Sample Tests of a Population Proportion: Two Sample Test of Differences in Population Means: Two Sample Test of Differences in Population Proportions: Issues in Testing Statistical HypothesesChapter 11: Statistical Association in Contingency TablesThe Importance of Statistical Association and Contingency TablesThe Structure of a Contingency TableDeveloping Tables of Total, Row, and Column PercentagesThe Rules for Interpreting a Contingency TableSpecifying Causal Relations in Contingency TablesAssessing the Magnitude of Bivariate Associations in Contingency TablesVisual and Intuitive Approach: The Chi-Square Test of Statistical Independence: Issues in Contingency Table AnalysisHow Many Categories for Categorical Variables?: GIGO and the Value of Theory in Identifying Other Important Variables: Sample Size and Significance Tests: Other Measures of Association for Categorical Variables: Chapter 12: The Analysis of Variance (ANOVA)Overview of ANOVA and When It Is UsedPartitioning Variation into Between- and Within- Group DifferencesCalculating the Total Variation in a Dependent Variable: Calculating the Between-Group Variation: Calculating the Within-Group Variation: Hypothesis Testing and Measures of Association in ANOVATesting the Hypothesis of Equality of Group Means: Measures of Association in ANOVA: Issues in the Analysis of VarianceChapter 13: Correlation and RegressionThe Scatterplot of Two Interval or Ratio VariablesThe Correlation Coefficient Regression AnalysisThe Computation of the Regression: Coefficient and Y-Intercept: Goodness of Fit of a Regression Equation: Hypothesis Testing and Tests of Statistical Significance: Using Regression Analysis for Predicting Outcomes: Issues in Bivariate Regression and Correlation AnalysisChapter 14: Introduction to Multivariate AnalysisWhy Do Multivariate Analysis?Exploring Multiple Causes: Statistical Control: Types of Multivariate AnalysisMultivariate Contingency Table Analysis: Partial Correlation Coefficients: Multiple Regression Analysis:.