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Intermediate Statistics For Dummies
by Deborah Rumsey
EDUCATION / CURRICULUM TOOLS / MATHEMATICS /
Need to know how to build and test models based on data? Intermediate Statistics For Dummies gives you the knowledge to estimate, investigate, correlate, and congregate certain variables based on the information at hand. The techniques you¡¯ll learn in this book are the same techniques used by professionals in medical and scientific fields.
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¡ªall 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¡ªfrom biology and engineering to business and politics!
Deborah Rumsey has a PhD in Statistics from The Ohio State University (1993). She is a Statistics Education Specialist/Auxiliary Faculty Member for the Department of Statistics. Dr. Rumsey has been given the distinction of being named a Fellow of the American Statistical Association. She has also won the Presidential Teaching Award from Kansas State University. She is the author of Statistics For Dummies, Statistics Workbook For Dummies, and Probability For Dummies. She has published numerous papers and given many professional presentations on the subject of statistics education. Her passions include being with her family, bird watching, solving Sudoku puzzles, getting more seat time on her Kubota tractor, and cheering the Ohio State Buckeyes on to another National Championship.
TABLE OF CONTENTS:
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.