Curricular Guide: OpenIntro Statistics, Diez et al., 4th edition

The book is online and available here.

This document is keyed to the table of contents of the book.

1 Introduction to data

• 1.1 Case study: using stents to prevent strokes

• 1.2 Data basics

  • Activity: Response and Explanatory Variables

• 1.3 Sampling principles and strategies

• 1.4 Experiments

  • Activity: Sampling Bias and the Confidence Interval
  • Acitivy: Intervention and Prediction

Extended comments

2 Summarizing data

• 2.1 Examining numerical data
  • Activity: Data and Point Plots
  • Activity: Shapes of distributions
• 2.2 Considering categorical data
  • Activity: Data and Point Plots
• 2.3 Case study: malaria vaccine

Extended comments

3 Probability

• 3.1 Defining probability
• 3.2 Conditional probability
• 3.3 Sampling from a small population
• 3.4 Random variables
• 3.5 Continuous distributions

Extended comments

4 Distributions of random variables

• 4.1 Normal distribution
  • Activity: Parameters and the Normal Distribution
  • ActivityCommon, Uncommon, and Rare
• 4.2 Geometric distribution
• 4.3 Binomial distribution
• 4.4 Negative binomial distribution
• 4.5 Poisson distribution

Extended comments

5 Foundations for inference

• 5.1 Point estimates and sampling variability
  • Activity: What is a Confidence Interval
  • Activity: Sampling Bias and the Confidence Interval
• 5.2 Confidence intervals for a proportion
• 5.3 Hypothesis testing for a proportion

Extended comments

6 Inference for categorical data

• 6.1 Inference for a single proportion
• 6.2 Difference of two proportions
• 6.3 Testing for goodness of fit using chi-square
• 6.4 Testing for independence in two-way tables

Extended comments

7 Inference for numerical data

• 7.1 One-sample means with the t-distribution
• 7.2 Paired data
  • Activity: Comparing Two Confidence Intervals
  • Activity: Comparing Two Groups
• 7.4 Power calculations for a difference of means
• 7.5 Comparing many means with ANOVA

Extended comments

8 Introduction to linear regression

• 8.1 Fitting a line, residuals, and correlation
  • Activity: Introducing Linear Regression
  • Activity: Describing Relationship Patterns in Words and Numbers
  • Activity: How much is explained?
• 8.2 Least squares regression
• 8.3 Types of outliers in linear regression
• 8.4 Inference for linear regression

Extended comments

9 Multiple and logistic regression

• 9.1 Introduction to multiple regression
  • Activity: Introducing Linear Regression
  • Activity: Describing Relationship Patterns in Words and Numbers
• 9.2 Model selection
• 9.3 Checking model conditions using graphs
• 9.4 Multiple regression case study: Mario Kart
• 9.5 Introduction to logistic regression

Extended comments