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
**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 10.3 Hypothesis Tests for a Population Mean
- Section 10.3A Using Simulation and the Bootstrap to Perform Hypothesis Tests on 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 Inference about Two Population Proportions
- Section 11.2 Inference about Two Means: Dependent Samples
- Section 11.2A Using Bootstrapping to Conduct Inference on Two Dependent Means
- Section 11.3A Using Randomization Techniques to Compare Two Independent Means
- Section 11.3 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
- Chapter 14