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Math and Computer ScienceStatistics

AP Statistics

Use the statistical problem-solving process to formulate questions, collect and analyze data, quantify uncertainty, and justify conclusions.

Start with the course map All AP courses

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Open a section, then choose the exact idea.

1Exploring One-Variable Data and Collecting Data13 topics

Frame investigative questions, summarize a single variable, compare distributions, and evaluate sampling and experimental designs.

  1. 1.1Introducing Statistics: What Can We Learn from Data?
  2. 1.2Variables
  3. 1.3Tabular Representation and Summary Statistics for One Categorical Variable
  4. 1.4Graphical Representations for One Categorical Variable
  5. 1.5Graphical Representations for One Quantitative Variable
  6. 1.6Descriptions for One Quantitative Variable Distributions
  7. 1.7Summary Statistics for One Quantitative Variable
  8. 1.8Graphical Representations of Summary Statistics for One Quantitative Variable
  9. 1.9Comparisons of the Distributions for One Quantitative Variable
  10. 1.10The Investigative Question Revisited and Data Collection
  11. 1.11Random Sampling
  12. 1.12Potential Problems with Sampling
  13. 1.13Experimental Design

2Probability, Random Variables, and Probability Distributions12 topics

Use simulation and probability rules to reason about categorical relationships, random variables, common distributions, and sampling behavior.

  1. 2.1Tabular and Graphical Representations for the Distributions of Two Categorical Variables
  2. 2.2Summary Statistics for Two Categorical Variables
  3. 2.3Estimating Probabilities Using Simulation
  4. 2.4Introduction to Probability
  5. 2.5Mutually Exclusive Events
  6. 2.6Conditional Probability
  7. 2.7Independent Events and Unions of Events
  8. 2.8Introduction to Random Variables and Probability Distributions
  9. 2.9Parameters of Random Variables
  10. 2.10The Binomial Distribution
  11. 2.11The Normal Distribution
  12. 2.12Sampling Distributions and the Central Limit Theorem

3Inference for Categorical Data: Proportions15 topics

Construct and interpret confidence intervals and tests for one or two proportions, including error analysis and chi-square procedures.

  1. 3.1Estimators
  2. 3.2Sampling Distributions for Sample Proportions
  3. 3.3Constructing a Confidence Interval for a Population Proportion
  4. 3.4Justifying a Claim Based on a Confidence Interval for a Population Proportion
  5. 3.5Setting Up a Test for a Population Proportion
  6. 3.6p-Values
  7. 3.7Carrying Out a Test for a Population Proportion
  8. 3.8Potential Errors When Performing Tests
  9. 3.9Sampling Distributions for the Difference Between Sample Proportions
  10. 3.10Constructing a Confidence Interval for the Difference Between Two Population Proportions
  11. 3.11Justifying a Claim Based on a Confidence Interval for the Difference Between Two Population Proportions
  12. 3.12Setting Up a Test for the Difference Between Two Population Proportions
  13. 3.13Carrying Out a Test for the Difference Between Two Population Proportions
  14. 3.14Setting Up a Chi-Square Test for Homogeneity or Independence
  15. 3.15Carrying Out a Chi-Square Test for Homogeneity or Independence

4Inference for Quantitative Data: Means10 topics

Apply sampling distributions, confidence intervals, and significance tests to one mean, paired means, and differences between independent means.

  1. 4.1Sampling Distributions for Sample Means
  2. 4.2Constructing a Confidence Interval for a Population Mean or Population Mean Difference
  3. 4.3Justifying a Claim Based on a Confidence Interval for a Population Mean or Population Mean Difference
  4. 4.4Setting Up a Test for a Population Mean or Population Mean Difference
  5. 4.5Carrying Out a Test for a Population Mean or Population Mean Difference
  6. 4.6Sampling Distributions for the Difference Between Two Sample Means
  7. 4.7Constructing a Confidence Interval for the Difference Between Two Population Means
  8. 4.8Justifying a Claim Based on a Confidence Interval for the Difference Between Two Population Means
  9. 4.9Setting Up a Test for the Difference Between Two Population Means
  10. 4.10Carrying Out a Test for the Difference Between Two Population Means

5Regression Analysis5 topics

Describe relationships between quantitative variables and assess linear models through correlation, residuals, and least-squares regression.

  1. 5.1Graphical Representations Between Two Quantitative Variables
  2. 5.2Correlation
  3. 5.3Linear Regression Models
  4. 5.4Residuals
  5. 5.5Least-Squares Regression