Statistics II for Dummies
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Part I: Tackling Data Analysis and Model-Building Basics.
Chapter 1: Beyond Number Crunching: The Art and Science of Data Analysis.
Chapter 2: Finding the Right Analysis for the Job.
Chapter 3: Reviewing Confi dence Intervals and Hypothesis Tests.
Part II: Using Different Types of Regression to Make Predictions.
Chapter 4: Getting in Line with Simple Linear Regression.
Chapter 5: Multiple Regression with Two X Variables.
Chapter 6: How Can I Miss You If You Won’t Leave? Regression Model Selection.
Chapter 7: Getting Ahead of the Learning Curve with Nonlinear Regressio.
Chapter 8: Yes, No, Maybe So: Making Predictions by Using Logistic Regression.
Part III: Analyzing Variance with ANOVA.
Chapter 9: Testing Lots of Means? Come On Over to ANOVA!
Chapter 10: Sorting Out the Means with Multiple Comparisons.
Chapter 11: Finding Your Way through Two-Way ANOVA.
Chapter 12: Regression and ANOVA: Surprise Relatives!
Part IV: Building Strong Connections with Chi-Square Tests.
Chapter 13: Forming Associations with Two-Way Tables.
Chapter 14: Being Independent Enough for the Chi-Square Test.
Chapter 15: Using Chi-Square Tests for Goodness-of-Fit (Your Data, Not Your Jeans).
Part V: Nonparametric Statistics: Rebels without a Distribution.
Chapter 16: Going Nonparametric.
Chapter 17: All Signs Point to the Sign Test and Signed Rank Test.
Chapter 18: Pulling Rank with the Rank Sum Test.
Chapter 19: Do the Kruskal-Wallis and Rank the Sums with the Wilcoxon.
Chapter 20: Pointing Out Correlations with Spearman's Rank.
Part VI: The Part of Tens.
Chapter 21: Ten Common Errors in Statistical Conclusions.
Chapter 22: Ten Ways to Get Ahead by Knowing Statistics.
Chapter 23: Ten Cool Jobs That Use Statistics.
Appendix: Reference Tables.
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