R All-in-One For Dummies

Book 3

Analyzing Data

Contents at a Glance

1. Chapter 1: The Confidence Game: Estimation
   1. Understanding Sampling Distributions
   2. An EXTREMELY Important Idea: The Central Limit Theorem
   3. Confidence: It Has Its Limits!
   4. Fit to a t
2. Chapter 2: One-Sample Hypothesis Testing
   1. Hypotheses, Tests, and Errors
   2. Hypothesis Tests and Sampling Distributions
   3. Catching Some Z’s Again
   4. Z Testing in R
   5. t for One
   6. t Testing in R
   7. Working with t-Distributions
   8. Visualizing t-Distributions
   9. Testing a Variance
   10. Working with Chi-Square Distributions
   11. Visualizing Chi-Square Distributions
3. Chapter 3: Two-Sample Hypothesis Testing
   1. Hypotheses Built for Two
   2. Sampling Distributions Revisited
   3. t for Two
   4. Like Peas in a Pod: Equal Variances
   5. t-Testing in R
   6. A Matched Set: Hypothesis Testing for Paired Samples
   7. Paired Sample t-testing in R
   8. Testing Two Variances
   9. Working with F Distributions
   10. Visualizing F Distributions
4. Chapter 4: Testing More than Two Samples
   1. Testing More than Two
   2. ANOVA in R
   3. Another Kind of Hypothesis, Another Kind of Test
   4. Getting Trendy
   5. Trend Analysis in R
5. Chapter 5: More Complicated Testing
   1. Cracking the Combinations
   2. Two-Way ANOVA in R
   3. Two Kinds of Variables … at Once
   4. After the Analysis
   5. Multivariate Analysis of Variance
6. Chapter 6: Regression: Linear, Multiple, and the General Linear Model
   1. The Plot of Scatter
   2. Graphing Lines
   3. Regression: What a Line!
   4. Linear Regression in R
   5. Juggling Many Relationships at Once: Multiple Regression
   6. ANOVA: Another Look
   7. Analysis of Covariance: The Final Component of the GLM
   8. But Wait — There’s ...