Curriculum Map

AP Statistics

College-level statistics covering data analysis, study design, probability, and inference. Aligned to the College Board AP Statistics Course and Exam Description. Equivalent to an introductory college statistics course.

14 Units

Early Units (Foundation)

Building Skills

Advanced Concepts

Capstone/Synthesis

Exploring Categorical Data

Summarize and display categorical data using frequency tables, bar charts, and pie charts, and draw conclusions from distributions.

3-4 days

Displaying Quantitative Data: Distributions

Construct and interpret dotplots, histograms, and stemplots, and describe distributions using shape, center, spread, and unusual features.

3-4 days

Describing Quantitative Data with Numbers

Calculate and interpret measures of center and spread including mean, median, standard deviation, IQR, and construct boxplots to summarize quantitative distributions.

4-5 days

The Normal Distribution

Use the normal distribution model to calculate probabilities and percentiles using z-scores, the empirical rule, and standard normal tables.

4-5 days

Exploring Bivariate Data: Correlation and Regression

Analyze relationships between two quantitative variables using scatterplots, correlation, and least-squares regression, including residual analysis.

5-6 days

Collecting Data: Sampling Methods and Study Design

Evaluate sampling methods for bias, distinguish observational studies from experiments, and understand how study design affects the conclusions we can draw.

4-5 days

Experimental Design

Design experiments using control, randomization, and replication to establish causation, and evaluate the validity of experimental conclusions.

3-4 days

Probability: The Foundation of Inference

Apply probability rules, conditional probability, and independence to calculate and interpret probabilities in real-world contexts.

5-6 days

Random Variables and Probability Distributions

Define discrete and continuous random variables, calculate expected value and variance, and apply rules for combining random variables.

4-5 days

Binomial and Geometric Distributions

Calculate and interpret probabilities, means, and standard deviations for binomial and geometric distributions in context.

4-5 days

Sampling Distributions and the Central Limit Theorem

Understand sampling distributions of sample means and proportions, and apply the Central Limit Theorem to describe their behavior.

5-6 days

Confidence Intervals for Proportions and Means

Construct and interpret confidence intervals for population proportions and means, and understand the effect of confidence level and sample size on interval width.

5-6 days

Hypothesis Testing: Significance Tests

Conduct and interpret one-sample significance tests for proportions and means, including p-values, significance levels, and Type I and Type II errors.

5-6 days

Inference for Two Samples, Chi-Square, and Regression

Extend inference to two-sample comparisons, chi-square tests for categorical data, and tests for slope in linear regression.

6-7 days

Learning Progression

This course is designed to be taken sequentially. Earlier units establish foundational concepts that later units build upon. While you can explore units in any order, following the numbered sequence provides the most coherent learning experience.