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AP Statistics
7 sections available · 39 chapters available
Free AP Statistics revision notes for AP (Advanced Placement) students. Each chapter covers a key topic with worked examples and practice prompts you can take straight into the thinka app.
Unit 1: Exploring One-Variable Data and Collecting Data
Statistical questions and variables
One categorical variable: tables and graphs
Graphical representations for one quantitative variable
Describing distributions of one quantitative variable
Summary statistics and relative position
Comparing distributions across groups
Random sampling and problems with sampling
Experimental design
Course Content
Unit 9: Inference for Quantitative Data: Slopes
Unit 2: Probability, Random Variables, and Probability Distributions
Two categorical variables: tables and summary statistics
Simulation and introduction to probability
Mutually exclusive events, unions, and independence
Conditional probability
Random variables and their parameters
The binomial distribution
The normal distribution
Sampling distributions and the Central Limit Theorem
Unit 3: Inference for Categorical Data: Proportions
Estimators and sampling distributions for sample proportions
Confidence intervals for a population proportion
Significance tests for a population proportion
p-values, Type I and Type II errors
Confidence intervals for a difference between two proportions
Tests for a difference between two proportions
Chi-square tests for homogeneity or independence
Unit 4: Inference for Quantitative Data: Means
Sampling distributions for sample means
Confidence intervals for a mean or mean difference
Tests for a mean or mean difference
Sampling distributions for a difference between two means
Confidence intervals for a difference between two means
Tests for a difference between two means
Unit 5: Regression Analysis
Scatterplots and describing association
Correlation
Linear regression models and prediction
Residuals and residual plots
Least-squares regression and r-squared
Statistical Practices and Exam Skills
Formulating an investigative question
Identifying and justifying data collection methods
Choosing an inference method and verifying conditions
Interpreting results and justifying claims in context
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