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| Measurement Invalidity | |
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| Sampling Problems | |
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| Faulty Causal Inferences | |
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| Political Influences | |
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| Human Fallibility | |
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| Issues in Data Preparation | |
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| Why Is Data Preparation Important? | |
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| Operationalization and Measurement | |
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| Nominal Measurement of Qualitative Variables | |
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| Measurement of Quantitative Variables | |
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| Issues in Levels of Measurement | |
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| Coding and Inputting Statistical Data | |
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| Available Computer Software for Basic Data Analysis | |
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| Displaying Data in Tables and Graphic forms | |
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| The Importance Of Data Tables and Graphs | |
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| Types of Tabular and Visual Presentations | |
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| Tables and Graphs for Qualitative Variables | |
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| Tables and Graphs for Quantitative Variables | |
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| Ratios and Rates | |
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| Maps of Qualitative and Quantitative Variables | |
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| Hazards and Distortions in Visual Displays and Collapsing Categories | |
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| Modes, Medians, Means, and More Modes and Modal Categories | |
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| The Median and Other Measures of Location | |
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| The Mean and Its Meaning Weighted Means | |
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| Strengths and Limitations of Mean Ratings | |
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| Choice of Measure of Central Tendency and Position | |
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| Measures of Variation and Dispersion | |
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| The Range of Scores | |
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| The Variance and Standard Deviation | |
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| Variances and Standard Deviations for Binary Variables | |
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| Population versus Sample Variances and Standard Deviations | |
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| The Normal Curve and Sampling Distributions | |
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| The Normal CurveZ-Scores as Standard Scores | |
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| Reading a Normal Curve Table | |
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| Other Sampling Distributions | |
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| Binomial Distributiont-Distribution | |
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| Chi-Square Distribution | |
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| F-Distribution | |
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| Parameter Estimation and Confidence Intervals | |
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| Sampling Distributions and the Logic of Parameter Estimation | |
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| Inferences from Sampling Distributions to One Real Sample | |
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| Confidence Intervals: Large Samples, Known | |
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| Confidence Intervals for Population Means | |
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| Confidence Intervals for Population Proportions | |
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| Confidence Intervals: Small Samples and Unknown | |
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| Properties of the t-Distribution | |
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| Confidence Intervals for Population Means for Unknown | |
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| Confidence Intervals for PopulationProportion for Unknown | |
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| Introduction to Hypothesis Testing | |
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| Confidence Intervals Versus Hypothesis Testing | |
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| Basic Terminology and Symbols | |
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| Types of Hypotheses | |
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| Zone of Rejection and Critical Values | |
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| Significance Levels and Errors in Decision-Making | |
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| Hypothesis Testing for Means and Proportions | |
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| Types of Hypothesis Testing | |
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| One-Sample Tests of the Population Mean | |
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| One-Sample Tests of a Population Proportion | |
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| Two Sample Test of Differences in Population Means | |
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| Two Sample Tests of Differences in Population Proportions | |
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| Issues in Testing Statistical Hypotheses | |
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| Statistical Association in Contingency Tables | |
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| The Importance of Statistical Association and Contingency Tables | |
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| The Structure of a Contingency Table | |
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| Developing Tables of Total, Row, and Column Percentages | |
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| The Rules for Interpreting a Contingency Table | |
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| Specifying Causal Relations in Contingency Tables | |
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| Assessing the Magnitude of Bivariate | |
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| Associations in Contingency Tables | |
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| Visual and Intuitive Approach | |
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| The Chi-Square Test of Statistical Independence | |
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| Issues in Contingency Table Analysis | |
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| How Many Categories for Categorical Variables? | |
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| GIGO and the Value of Theory in Identifying Variables | |
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| Sample Size and Significance Tests | |
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| Other Measures of Association for Categorical Variables | |
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| The Analysis of Variance (ANOVA) | |
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| Overview of ANOVA and When it is Used | |
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| Partitioning Variation into Between and Within Group Differences | |
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| Calculating the Total Variation in a Dependent Variable | |
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| Calculating the Between-Group Variation | |
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| Calculating the Within-Group Variation | |
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| Hypothesis Testing and Measures of Association in ANOVA | |
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| Testing the Hypothesis of Equality of Group Means | |
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| Measures of Association in ANOVA | |
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| Issues in the Analysis of Variance | |
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| Correlation and Regression | |
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| The Scatterplot of Two Interval/Ratio Variables | |
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| The Correlation Coefficient | |
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| Regression Analysis | |
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| The Computation of the Regression | |
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| Coefficient and Y-Intercept | |
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| Goodness of Fit of a Regression Equation | |
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| Hypothesis Testing and Tests of Statistical Significance | |
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| Using Regression Analysis for Predicting Outcomes | |
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| Issues in Bivariate Regression and Correlation Analysi | |
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| Intro | |