Intermediate Statistics for Dummies (For Dummies)

Picking up right where Statistics For Dummies left off, this straightforward, easy-to-follow book guides you beyond Central Limit Theorem and hypothesis tests and immerses you in flavors of regression, ANOVA, and nonparametric procedures. Unlike regular statistics books, this guide provides full explanations of intermediate statistical ideas; computer input dissection; an extensive number of examples, tips, strategies, and warnings; and clear, concise step-by-step procedures—all in a language you can understand. You’ll soon discover how to:

• Analyze data and base models off of your data
• Make predictions using regression
• Compare many means with ANOVA
• Test models using Chi-square
• Dealing with abnormal data

In addition, this book includes a list of wrong statistical conclusions and common questions that professors ask using computer output. This book also adopts a nonlinear approach, making it possible to skip to the information you need without having to read previous chapters. With Intermediate Statistics For Dummies, you’ll have all the tools you need to make important decisions in all types of professional areas—from biology and engineering to business and politics!

The statistics speak for themselves: enrollment in college statistics courses is up 45 percent over the last decade, the number of college-bound students taking the AP Statistics Exam nearly doubled from 2000 to 2003, and Statistics For Dummies has sold more than 65,000 copies in just over two years! This new guide takes statistics students to the next level, offering a refresher on statistics basics and covering concepts and topics typically encountered in second-semester statistics courses, including boxplots and scatterplots, Chebyshev's inequality, outliers, Z-scores, hypothesis tests, and Simpson's paradox.

Deborah Rumsey, PhD (Westerville, OH), is a Statistics Education Specialist and auxiliary faculty member at The Ohio State University. She is the author of Statistics For Dummies (0-7645-5423-9), Statistics Workbook For Dummies (0-7645-8466-9), and Probability For Dummies (0-471-75141-3).

Part I: Data Analysis and Model-Building Basics.

Chapter 1: Beyond Number Crunching: The Art and Science of Data Analysis.

Chapter 2: Sorting through Statistical Techniques.

Chapter 3: Building Confidence and Testing Models.

Part II: Making Predictions by Using Regression.

Chapter 4: Getting in Line with Simple Linear Regression.

Chapter 5: When Two Variables Are Better than One: Multiple Regression.

Chapter 6: One Step Forward and Two Steps Back: Regression Model Selection.

Chapter 7: When Data Throws You a Curve: Using Nonlinear Regression.

Chapter 8: Yes, No, Maybe So: Making Predictions By Using Logistic Regression.

Part III: Comparing Many Means with ANOVA.

Chapter 9: Going One-Way with Analysis of Variance.

Chapter 10: Pairing Things Down with Multiple Comparisons.

Chapter 11: Getting a Little Interaction with Two-Way ANOVA.

Chapter 12: Rock My World: Relating Regression to ANOVA.

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: Rebels without a Distribution.

Chapter 16: Going Nonparametric.

Chapter 17: 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 Wilcox.

Chapter 20: Pointing Out Correlations with Spearman’s Rank.

Part VI: The Part of Tens.

Chapter 21: Ten Errors in Statistical Conclusions.

Chapter 22: Ten Practice Problems.

Appendix: Tables for Your Reference.

Index.