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Learn to read data, design fair studies and make qualified statistical claims through complete explanations, labeled investigations and original practice. Units 1–5 follow the revised Fall 2026 AP Statistics framework.
Browse the study guide →STUDY GUIDE · APYour AP Statistics
Your AP Statistics
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Choose a unit, expand an official topic, and open a focused lesson. Units 1–5 are available as review editions. This guide follows the revised Fall 2026 framework.
5 units99 focused lessonsUnits 1–5 review editions
Teacher review pending
Teacher review pending
1 Exploring One-Variable Data and Collecting Data 21 lessons · Review edition
Follow a question from data collection to a defensible conclusion. Explore categorical and quantitative displays, summaries, comparisons, random sampling, bias and experimental design. 42 explained questions, 63 recall cards and 21 written challenges cover official topics 1.1–1.13. An optional 3D sampling map complements fully labeled 2D investigations. Fall 2026 framework. Independent teacher review and student testing remain pending.
1.1 Introducing Statistics: What Can We Learn from Data?
1.2 Variables
1.3 Tabular Representation and Summary Statistics for One Categorical Variable
1.4 Graphical Representations for One Categorical Variable
1.5 Graphical Representations for One Quantitative Variable
1.6 Descriptions for One Quantitative Variable Distributions
1.7 Summary Statistics for One Quantitative Variable
1.8 Graphical Representations of Summary Statistics for One Quantitative Variable
1.9 Comparisons of the Distributions for One Quantitative Variable
1.10 The Investigative Question Revisited and Data Collection
1.11 Random Sampling
1.12 Potential Problems with Sampling
1.13 Experimental Design
2 Probability, Random Variables, and Probability Distributions 23 lessons · Review edition
Begin with a two-way table and build toward probability models and repeated sampling. 46 explained questions, 69 recall cards and 23 written challenges cover official topics 2.1–2.12. Explore an optional 3D coin-toss outcome cube alongside complete 2D diagrams and tables. Fall 2026 framework. Independent teacher review and student testing remain pending.
2.1 Tabular and Graphical Representations for the Distributions of Two Categorical Variables
2.2 Summary Statistics for Two Categorical Variables
2.3 Estimating Probabilities Using Simulation
2.4 Introduction to Probability
2.5 Mutually Exclusive Events
2.6 Conditional Probability
2.7 Independent Events and Unions of Events
2.8 Introduction to Random Variables and Probability Distributions
2.9 Parameters of Random Variables
2.10 The Binomial Distribution
2.11 The Normal Distribution
2.12 Sampling Distributions and the Central Limit Theorem
3 Inference for Categorical Data: Proportions 23 lessons · Review edition
Learn how samples support qualified population claims. Explore one- and two-proportion confidence intervals, hypothesis tests, errors and power, and chi-square inference. 46 explained questions, 69 recall cards and 23 written challenges cover official topics 3.1–3.15. Optional 3D count-grid inspection complements complete 2D tables and models. Fall 2026 framework. Independent teacher review and student testing remain pending.
3.1 Estimators
3.2 Sampling Distributions for Sample Proportions
3.3 Constructing a Confidence Interval for a Population Proportion
3.4 Justifying a Claim Based on a Confidence Interval for a Population Proportion
3.5 Setting Up a Test for a Population Proportion
3.6 p-Values
3.7 Carrying Out a Test for a Population Proportion
3.8 Potential Errors When Performing Tests
3.9 Sampling Distributions for the Difference Between Sample Proportions
3.10 Constructing a Confidence Interval for the Difference Between Two Population Proportions
3.11 Justifying a Claim Based on a Confidence Interval for the Difference Between Two Population Proportions
3.12 Setting Up a Test for the Difference Between Two Population Proportions
3.13 Carrying Out a Test for the Difference Between Two Population Proportions
3.14 Setting Up a Chi-Square Test for Homogeneity or Independence
3.15 Carrying Out a Chi-Square Test for Homogeneity or Independence
4 Inference for Quantitative Data: Means 20 lessons · Review edition
Estimate and compare population averages. Explore sampling means, t distributions, paired differences, confidence intervals and independent-group tests. 40 explained questions, 60 recall cards and 20 written challenges cover official topics 4.1–4.10. Optional 3D paired-data inspection complements complete 2D tables and models. Fall 2026 framework. Independent teacher review and student testing remain pending.
4.1 Sampling Distributions for Sample Means
4.2 Constructing a Confidence Interval for a Population Mean or Population Mean Difference
4.3 Justifying a Claim Based on a Confidence Interval for a Population Mean or Population Mean Difference
4.4 Setting Up a Test for a Population Mean or Population Mean Difference
4.5 Carrying Out a Test for a Population Mean or Population Mean Difference
4.6 Sampling Distributions for the Difference Between Two Sample Means
4.7 Constructing a Confidence Interval for the Difference Between Two Population Means
4.8 Justifying a Claim Based on a Confidence Interval for the Difference Between Two Population Means
4.9 Setting Up a Test for the Difference Between Two Population Means
4.10 Carrying Out a Test for the Difference Between Two Population Means
5 Regression Analysis 12 lessons · Review edition
Connect paired data to scatterplots, correlation, predictions, residuals and least-squares regression. 24 explained questions, 36 recall cards and 12 written challenges cover official topics 5.1–5.5. An optional 3D least-squares surface complements complete 2D tables and models. Fall 2026 framework. Independent teacher review and student testing remain pending.
5.1 Graphical Representations Between Two Quantitative Variables
5.3 Linear Regression Models
5.4 Residuals
Curriculum sources & scope · AP Statistics
College Board
REVISED: Fall 2026 framework has five units.
Complete official content is in the CED unit guides, including topic IDs, learning objectives, essential knowledge and course skills. The outline on this page is navigation only.
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01 Exploring distributions and relationships
02 Study design and data collection
03 Probability and sampling distributions
04 Estimation, inference, and justified conclusions
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