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Intermediate Statistics for Dummies
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Introduction
Part I: Data Analysis and Model-Building Basics
Beyond Number Crunching: The Art and Science of Data Analysis
Sorting through Statistical Techniques
Building Confidence and Testing Models
Part II: Making Predictions by Using Regression
Getting in Line with Simple Linear Regression
When Two Variables Are Better than One: Multiple Regression
One Step Forward and Two Steps Back: Regression Model Selection
When Data Throws You a Curve: Using Nonlinear Regression
Yes, No, Maybe So: Making Predictions By Using Logistic Regression
Part III: Comparing Many Means with ANOVA
Going One-Way with Analysis of Variance
Pairing Things Down with Multiple Comparisons
Getting a Little Interaction with Two-Way ANOVA
Rock My World: Relating Regression to ANOVA
Part IV: Building Strong Connections with Chi-Square Tests
Forming Associations with Two-Way Tables
Being Independent Enough for the Chi-Square Test
Using Chi-Square Tests for Goodness-of-Fit (Your Data, Not Your Jeans)
Part V: Rebels without a Distribution
Going Nonparametric
The Sign Test and Signed Rank Test
Pulling Rank with the Rank Sum Test
Do the Kruskal-Wallis and Rank the Sum
Pointing Out Correlations with Spearman’s Rank
Part VI: The Part of Tens
Ten Errors in Statistical Conclusions
Ten Practice Problems
Appendix: Tables for Your Reference
Index
IITJEE Books
Statistics
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