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Precision.ġ8.4 Assumptions and Conditions.Ĭhapter 19 Testing Hypotheses About Proportions.ġ9.3 The Reasoning of Hypothesis Testing.ġ9.4 Alternative Alternatives.ġ9.5 P-Values and Decisions: What to Tell About a Hypothesis Test.Ĭhapter 20 Inferences About Means.Ģ0.1 Getting Started: The Central Limit Theorem (Again).Ģ0.4 A Hypothesis Test for the Mean.Ģ0.5 Choosing the Sample Size.Ģ1.2 How to Think About P-Values.Ģ1.4 Critical Values for Hypothesis Tests.Ĭhapter 22 Comparing Groups.Ģ2.1 The Standard Deviation of a Difference.Ģ2.2 Assumptions and Conditions for Comparing Proportions.Ģ2.3 A Confidence Interval for the Difference Between Two Proportions.Ģ2.4 The Two Sample z-Test: Testing for the Difference Between Proportions.Ģ2.5 A Confidence Interval for the Difference Between Two Means.Ģ2.6 The Two-Sample t-Test: Testing for the Difference Between Two Means.Ģ2.7 The Pooled t-Test: Everyone into the Pool?.Ĭhapter 23 Paired Samples and Blocks.Ģ3.2 Assumptions and Conditions.Ģ3.3 Confidence Intervals for Matched Pairs.Ģ4.2 Chi-Square Test of Homogeneity.Ģ4.3 Examining the Residuals.Ģ4.4 Chi-Square Test of Independence.Ĭhapter 25 Inferences for Regression.Ģ5.1 The Population and the Sample.Ģ5.2 Assumptions and Conditions.Ģ5.3 Intuition About Regression Inference.Ģ5.5 Standard Errors for Predicted Values.Ģ5.6 Confidence Intervals for Predicted Values.Ĭhapter *26 Analysis of Variance.Ģ6.1 Testing Whether the Means of Several Groups Are Equal.Ģ6.3 Assumptions and Conditions.Ģ6.5 ANOVA on Observational Data.Ĭhapter 27 Multifactor Analysis of Variance.Ģ7.1 A Two Factor ANOVA Model.Ģ7.2 Assumptions and Conditions.Ģ8.1 What Is Multiple Regression?.Ģ8.2 Interpreting Multiple Regression Coefficients.Ģ8.3 The Multiple Regression Model-Assumptions and Conditions.Ģ8.4 Multiple Regression Inference.Ģ8.5 Comparing Multiple Regression Models.Ĭhapter 29 Multiple Regression Wisdom (available online).Ģ9.2 Diagnosing Regression Models: Looking at the Cases.Ģ9.3 Building Multiple Regression Models.ĭ Tables and Selected Formulas. *6.4 Straightening Scatterplots.Ĭhapter 7 Linear Regression.ħ.1 Least Squares: The Line of “Best Fit”.ħ.3 Finding the Least Squares Line.ħ.5 Examining the Residuals.ħ.6 R2-The Variation Accounted For by the Model.ħ.7 Regression Assumptions and Conditions.Ĩ.2 Extrapolation: Reaching Beyond the Data.Ĩ.3 Outliers, Leverage, and Influence.Ĩ.4 Lurking Variables and Causation.Ĩ.5 Working with Summary Values.Ĭhapter 9 Re-expressing Data: Get It Straight!.ĩ.1 Straightening Scatterplots – The Four Goals.ĩ.2 Finding a Good Re-Expressio.Ĭhapter 10 Understanding Randomness.ġ1.1 The Three Big Ideas of Sampling.ġ1.2 Populations and Parameters.ġ1.4 Other Sampling Designs.ġ1.5 From the Population to the Sample: You Can’t Always Get What You Want.ġ1.7 Common Sampling Mistakes, or How to Sample Badly.ġ2.2 Randomized, Comparative Experiments.ġ2.3 The Four Principles of Experimental Design.ġ4.1 The General Addition Rule.ġ4.2 Conditional Probability and the General Multiplication Rule.ġ4.4 Picturing Probability: Tables, Venn Diagrams, and Trees.ġ4.5 Reversing the Conditioning and Bayes’ Rule.ġ5.1 Center: The Expected Value.ġ5.2 Spread: The Standard Deviation.ġ5.3 Shifting and Combining Random Variables.ġ5.4 Continuous Random Variables.ġ6.4 Approximating the Binomial with a Normal Model.ġ6.5 The Continuity Correction.ġ6.7 Other Continuous Random Variables: The Uniform and the Exponential.ġ7.1 Sampling Distribution of a Proportion.ġ7.2 When Does the Normal Model Work? Assumptions and Conditions.ġ7.3 The Sampling Distribution of Other Statistics.ġ7.4 The Central Limit Theorem: The Fundamental Theorem of Statistics.ġ7.5 Sampling Distributions: A Summary.Ĭhapter 18 Confidence Intervals for Proportions.ġ8.2 Interpreting Confidence Intervals: What Does 95% Confidence Really Mean?.ġ8.3 Margin of Error: Certainty vs.
Chapter 2 Displaying and Describing Categorical Data.Ģ.1 Summarizing and Displaying a Single Categorical Variable.Ģ.2 Exploring the Relationship Between Two Categorical Variables.ģ.1 Displaying Quantitative Variables.ģ.5 Boxplots and 5-Number Summaries.ģ.6 The Center of Symmetric Distributions: The Mean.ģ.7 The Spread of Symmetric Distributions: The Standard Deviation.ģ.8 Summary-What to Tell About a Quantitative Variable.Ĭhapter 4 Understanding and Comparing Distributions.Ĥ.1 Comparing Groups with Histograms.Ĥ.2 Comparing Groups with Boxplots.Ĥ.4 Timeplots: Order, Please!.Ĥ.5 Re-Expressing Data: A First Look.Ĭhapter 5 The Standard Deviation as a Ruler and the Normal Model.ĥ.1 Standardizing with z-Scores.ĥ.4 Finding Normal Percentiles.ĥ.5 Normal Probability Plots.Ĭhapter 6 Scatterplots, Association, and Correlation.Ħ.3 Warning: Correlation fi Causation.
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