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
    • Obtain a Simple Random Sample

• Chapter 2 Organizing and Summarizing Data
  • 2.1 Organizing Qualitative Data
    • Organize qualitative data in tables
    • Frequency and relative frequency bar graphs
    • Side-by-side bar graphs
    • Construct pie charts
  • 2.2 Organizing Quantitative Data: The Popular Displays
    • Organize discrete data in tables
    • Construct histograms of discrete data
    • Organize continuous data in tables
    • Construct histograms of continuous data
    • Draw dot plots
  • 2.3 Additional Displays of Quantitative Data
    • Draw stem-and-leaf plots
    • Construct a frequency polygon
    • Draw time-series graphs

• 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
    • Determine the range
    • Determine the standard deviation and variance
    • Comparing the standard deviation of two data sets (Example 6)
    • Using favstats( ) with Mosaic
  • 3.3 Measures of Central Tendency and Dispersion from Grouped Data
    • Approximate the mean and standard deviation from grouped data
    • Compute the weighted mean
  • 3.4 Measures of Position and Outliers
    • Determine quartiles
    • Determine the interquartile range (IQR)
  • 3.5 The Five-Number Summary and Boxplots
    • Compute the five-number summary
    • Draw boxplots
    • Draw boxplots with two or more categorical variables

• Chapter 4 Describing the Relation between Two Variables
  • 4.1 Scatter Diagrams and Correlation
    • Draw a scatter diagram
    • Determine the correlation coefficient
    • Working with qualitative (categorical) variables
    • Correlation matrix
  • 4.2 Least-Squares Regression
    • Finding least-squares regression line and making predictions
  • 4.3 Diagnostics on the Least-Squares Regression Line
    • Coefficient of Determination
    • Residual analysis
    • Influential observations
  • 4.4 Contingency Tables and Association
    • Marginal distributions
    • Conditional distributions
    • Conditional bar graphs

• Chapter 5 Probability
  • Section 5.5 Counting Techniques
  • Section 5.6 Simulation

• Chapter 6 Discrete Probability Distributions
  • Section 6.1 Discrete Random Variables
    • Graph Discrete Probability Distributions
    • Compute the Mean and Standard Deviation of a Discrete Probability Distribution
  • Section 6.2 The Binomial Probability Distribution
    • Obtain binomial probabilities
    • Graph a binomial probability distribution
  • Section 6.3 The Poisson Probability Distribution
    • Obtain Poisson probabilities

• Chapter 7 The Normal Probability Distribution
  • Section 7.1 Properties of the Normal Distribution
  • Section 7.2 Applications of the Normal Distribution
    • Find area under the normal curve
    • Find the value of a normal random variable
  • Section 7.3 Assessing Normality
    • Draw a normal probability plot
• Chapter 8 Sampling Distributions
  • Section 8.1 Distribution of the Sample Mean
    • Describe the Distribution of the Sample Mean: Normal Population
    • Describe the Distribution of the Sample Mean: Non-Normal Population
  • Section 8.2 Distribution of the Sample Proportion
    • Describe the Sampling Distribution of a Sample Proportion
• Chapter 9 Estimating the Value of a Parameter
  • Section 9.1 Estimating a Population Proportion
    • Construct a confidence interval for a population proportion
    • Determine sample size
  • Section 9.2 Estimating a Population Mean
    • Construct a confidence interval for a population mean
    • Determine sample size
  • Section 9.3 Estimating a Population Standard Deviation
    • Construct a confidence interval for a population standard deviation
  • Section 9.5 Estimating with Bootstrapping
    • Estimate a population mean using the bootstrap method
• Chapter 10 Hypothesis Test Regarding a Parameter
  • Section 10.2/10.2B Hypothesis Test for a Population Proportion
    • Test hypotheses about a population proportion
    • Test hypotheses about a population proportion using simulation
    • Test hypotheses about a population proportion using an Urn
  • Section 10.3 Hypothesis Tests for a Population Mean
    • Test hypotheses about a mean
  • Section 10.3A Using Simulation and the Bootstrap to Perform Hypothesis Tests on a Population Mean
    • Test hypotheses about a population mean using the simulation method
    • Test hypotheses about a population mean using the bootstrap
  • Section 10.4 Hypothesis Tests for a Population Standard Deviation
    • Test hypotheses about a population standard deviation
• Chapter 11 Inference about Two Population Parameters
  • Section 11.1A Use Randomization Techniques to Compare Two Proportions
    • Use randomization to compare two population proportions
  • Section 11.1 Inference about Two Population Proportions
    • Test hypotheses regarding two proportions from independent samples
    • Construct confidence intervals for the difference between 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
    • Use randomization to compare two population means
  • Section 11.3 Inference about Two Means: Independent Samples
    • Test hypotheses regarding the difference of two independent means
    • Construct confidence intervals regarding the difference of two independent means
  • 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
    • Perform a test for independence
    • Perform a test for homogeneity of proportions
  • Section 12.3 Inference about Two Population Proportions: Dependent Samples
• Chapter 13
• Chapter 14