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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 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
Deborah Rumsey, PhD, is a Statistics Education Specialist and Auxiliary Faculty Member in the Department of Statistics at Ohio State University. She is also a Fellow of the American Statistical Association and has received the Presidential Teaching Award from Kansas State University. Dr. Rumsey has published numerous papers and given many professional presentations on the subject of statistics education.
