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| Introduction: Variables and Processes in Statistics | |
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| Types of Variables: Categorical or Quantitative | |
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| Students Talk Stats: Identifying Types of Variables | |
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| Handling | |
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| Data for Two Types of Variables | |
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| Roles of Variables: Explanatory or Response | |
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| Statistics as a Four-Stage Process | |
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| Data Production | |
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| Sampling: Which Individuals Are Studied | |
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| Sources of Bias in Sampling: When Selected Individuals Are Not Representative | |
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| Probability Sampling Plans: Relying on Randomness | |
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| Role of Sample Size: Bigger Is Better if the Sample Is Representative | |
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| From Sample to Population: To What Extent Can We Generalize? | |
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| Students Talk Stats: Seeking a Representative Sample | |
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| Design: How Individuals Are Studied | |
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| Various Designs for Studying Variables | |
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| Sample Surveys: When Individuals Report Their Own Values | |
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| Observational Studies: When Nature Takes Its Course | |
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| Experiments: When Researchers Take Control | |
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| Students Talk Stats: Does TV Cause ADHD? | |
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| Considering Study Design | |
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| Displaying and Summarizing Data | |
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| Displaying and Summarizing Data for a Single Variable | |
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| Single Categorical Variable | |
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| Students Talk Stats: Biased Sample, Biased Assessment | |
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| Single Quantitative Variables and the Shape of a Distribution | |
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| Center and Spread: What's Typical for Quantitative Values, and How They Vary | |
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| Normal Distributions: The Shape of Things to Come | |
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| Displaying and Summarizing Relationships | |
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| Relationship Between One Categorical and One Quantitative Variable | |
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| Students Talk Stats: Displaying and Summarizing Paired Data | |
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| Relationship Between Two Categorical Variables | |
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| Relationships Between Two Quantitative Variables | |
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| Students Talk Stats: How Outliers and Influential Observations Affect a Relationship | |
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| Students Talk Stats: Confounding in a Relationship Between Two Quantitative Variables | |
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| Probability | |
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| Finding Probabilities | |
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| The Meaning of "Probability" and Basic Rules | |
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| More General Probability Rules and Conditional Probability | |
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| Students Talk Stats: Probability as a Weighted Average of Conditional Probabilities | |
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| Random Variables | |
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| Discrete Random Variables | |
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| Binomial Random Variables | |
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| Students Talk Stats: Calculating and Interpreting the Mean and Standard Deviation of Count or Proportion | |
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| Continuous Random Variables and the Normal Distribution | |
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| Students Talk Stats: Means, Standard Deviations, and Below-Average Heights | |
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| Sampling Distributions | |
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| The Behavior of Sample Proportion in Repeated Random Samples | |
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| The Behavior of Sample Mean in Repeated Random Samples | |
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| Students Talk Stats: When Normal Approximations Are Appropriate | |
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| Statistical Inference | |
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| Inference for a Single Categorical Variable | |
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| Point Estimate and Confidence Interval: A Best Guess and a Range of Plausible Values for Population Proportion | |
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| Students Talk Stats: Interpreting a Confidence Interval | |
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| Test: Is a Proposed Population Proportion Plausible? | |
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| Students Talk Stats: Interpreting a P-value | |
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| Students Talk Stats: What Type of Error Was Made? | |
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| Students Talk Stats: The Correct Interpretation of a Small P-value | |
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| Students Talk Stats: The Correct Interpretation When a P-value Is Not Small | |
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| Inference for a Single Quantitative Variable | |
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| Inference for a Mean when Population Standard Deviation Is Known or Sample Size Is Large | |
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| Students Talk Stats: Confidence Interval for a Mean | |
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| Students Talk Stats: Interpreting a Confidence Interval for the Mean Correctly | |
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| Inference for a Mean When the Population Standard Deviation Is Unknown and the Sample Size Is Small | |
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| Students Talk Stats: Practical Application of a t Test | |
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| A Closer Look at Inference for Means | |
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| Inference for Relationships Between Categorical and Quantitative Variables | |
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| Inference for a Paired Design with t | |
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| Inference for a Two-Sample Design with t | |
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| Students Talk Stats: Ordinary vs. Pooled Two-Sample t | |
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| Inference for a Several-sample Design with F: Analysis of Variance | |
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| Students Talk Stats: Reviewing Relationships between Categorical and Quantitative Variables | |
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| Inference for Relationships Between Two Categorical Variables | |
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| Comparing Proportions with a z Test | |
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| Comparing Counts with a Chi-Square Test | |
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| Inference for Relationships Between Two Quantitative Variables | |
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| Inference for Regression: Focus on the Slope of the Regression Line | |
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| Students Talk Stats: No Evidence of a Relationship | |
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| Interval Estimates for an Individual or Mean Response | |
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| How Statistics Problems Fit into the Big Picture | |
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| The Big Picture in Problem-Solving | |
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| Students Talk Stats: Choosing the Appropriate Statistical Tools | |
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| Non-Parametric Methods (Online) | |
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| The Sign Test as an Alternative to the Paired t Test | |
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| The Rank-Sum Test as an Alternative to the Two-Sample t Test | |
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| Summary of Non-Parametrics | |
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| Two-Way ANOVA (Online) | |
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| Multiple Regression (Online) | |
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| Solutions to Selected Exercises | |