The ideal supplement and study guide for students preparing for advanced statistics Packed with fresh and practical examples appropriate for a range of degree-seeking students, Statistics II For Dummies helps any reader succeed in an upper-level statistics course. It picks up with data analysis where Statistics For Dummies left off, featuring new and updated examples, real-world applications, and test-taking strategies for success. This easy-to-understand guide covers such key topics as sorting and testing models, using regression to make predictions, performing variance analysis (ANOVA), drawing test conclusions with chi-squares, and making comparisons with the Rank Sum Test.
Introduction. 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. Index.
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