Here is an R Guidebook that may be used in conjunction with any of the Sullivan Statistics titles.

- How to post data in Github
- Introduction to R (Stats 6e)
- Introduction to R (Stats 7e)
**Chapter 1 Data Collection**- 1.3 Simple Random Sampling

**Chapter 2 Organizing and Summarizing Data**- 2.1 Organizing Qualitative Data
- 2.2 Organizing Quantitative Data: The Popular Displays
- 2.3 Additional Displays of Quantitative Data

**Chapter 3 Numerically Summarizing Data**- 3.1 Measures of Central Tendency
- Determine the Arithmetic Mean
- Determine the Median
- Explain What It Means for a Statistic to be Resistant
- Determine the Mode
- Finding Measures of Center by a Qualitative Variable

- 3.2 Measures of Dispersion
- 3.3 Measures of Central Tendency and Dispersion from Grouped Data
- 3.4 Measures of Position and Outliers
- 3.5 The Five-Number Summary and Boxplots

- 3.1 Measures of Central Tendency

**Chapter 4 Describing the Relation between Two Variables**- 4.1 Scatter Diagrams and Correlation
- 4.2 Least-Squares Regression
- 4.3 Diagnostics on the Least-Squares Regression Line
- 4.4 Contingency Tables and Association

**Chapter 5 Probability**- Section 5.5 Counting Techniques
- Section 5.6 Simulation

**Chapter 6 Discrete Probability Distributions**- Section 6.1 Discrete Random Variables
- Section 6.2 The Binomial Probability Distribution
- Section 6.3 The Poisson Probability Distribution

**Chapter 7 The Normal Probability Distribution**- Section 7.1 Properties of the Normal Distribution
- Section 7.2 Applications of the Normal Distribution
- Section 7.3 Assessing Normality

**Chapter 8 Sampling Distributions**- Section 8.1 Distribution of the Sample Mean
- Section 8.2 Distribution of the Sample Proportion

**Chapter 9 Estimating the Value of a Parameter**- Section 9.1 Estimating a Population Proportion
- Section 9.2 Estimating a Population Mean
- Section 9.3 Estimating a Population Standard Deviation
- Section 9.5 Estimating with Bootstrapping

**Chapter 10 Hypothesis Test Regarding a Parameter**- Section 10.2/10.2B Hypothesis Test for a Population Proportion
- Section 10.3A Using Simulation and the Bootstrap to Perform Hypothesis Tests on a Population Mean
- Section 10.3/10.3B Hypothesis Tests for a Population Mean
- Section 10.4 Hypothesis Tests for a Population Standard Deviation

**Chapter 11 Inference about Two Population Parameters**- Section 11.1A Use Randomization Techniques to Compare Two Proportions
- Section 11.1/11.1B Inference about Two Population Proportions
- Section 11.2A Using Bootstrapping to Conduct Inference on Two Dependent Means
- Section 11.2/11.2B Inference about Two Means: Dependent Samples
- Section 11.3A Using Randomization Techniques to Compare Two Independent Means
- Section 11.3/11.3B Inference about Two Means: Independent Samples
- Section 11.4 Inference about Two Population Standard Deviations

**Chapter 12 Inference on Categorical Data**- Section 12.1 Goodness-of-Fit Test
- Section 12.2 Tests for Independence and the Homogeneity of Proportions
- Section 12.3 Inference about Two Population Proportions: Dependent Samples

**Chapter 13 Comparing Three or More Means**- Section 13.1 Comparing Three or More Means (One-Way Analysis of Variance)
- Section 13.2 Post Hoc Tests on One-Way Analysis of Variance
- Section 13.3 The Randomized Complete Block Design
- Section 13.4 Two-Way Analysis of Variance

**Chapter 14 Inference on the Least-Squares Regression Model and Multiple Regression**- Section 14.1A Using Randomization Techniques on the Slope of the Least-Squares Regression Model
- Section 14.1 Testing the Significance of the Least-Squares Regression Model
- Section 14.2 Confidence and Prediction Intervals
- Section 14.3 Introduction to Multiple Regression
- Section 14.4 Interaction and Dummy Variables
- Section 14.5 Polynomial Regression
- Section 14.6 Building a Regression Model

**Chapter 15 Nonparametric Statistics**- Section 15.2 Runs Test
- Section 15.3 Inference about Measures of Central Tendency
- Section 15.4 Inference about the Difference between Two Medians: Dependent Samples
- Example 1: Wilcoxon Matched-Pairs Signed-Rank Test
- Example 2: Wilcoxon One-Sample Ranked-Sum Test

- Section 15.5 Inference about the Difference between Two Medians: Independent Samples
- Section 15.6 Spearman's Rank-Correlation Test
- Section 15.7 Kruskal-Wallis Test