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About the Course
Statistics are a part of everyday life. You can see them in AI models, news polls, popular music rankings, and medical research. Discover how the statistics you see every day are developed and learn how to evaluate their credibility for yourself in AP Statistics.
Skills You'll Learn
Selecting methods for collecting or analyzing data
Describing patterns, trends, associations, and relationships in data
Using probability and simulation to describe probability distributions and define uncertainty in statistical inference
Using statistical reasoning to draw appropriate conclusions and justify claims
Equivalency and Prerequisites
College Course Equivalent
A one-semester, introductory, non-calculus-based college course in statistics
Recommended Prerequisites
A first-year algebra course
Exam Date
AP Statistics Exam
This is the regularly scheduled date for the AP Statistics Exam.
Your Future Starts Now
AP can lead to a wide range of careers and college majors.
About the Units
The course content outlined below is organized into commonly taught units of study that provide one possible sequence for the course. Your teacher may choose to organize the course content differently based on local priorities and preferences.
Course Content
Unit 1: Exploring One-Variable Data and Collecting Data
You will formulate investigative questions, represent categorical and quantitative variables, compare distributions of one-variable data, interpret calculations to assess claims, and justify the use of experimental design principles.
Topics may include:
- Variables
- Tabular Representation and Summary Statistics for One Categorical Variable
- Graphical Representations for One Categorical Variable
- Graphical Representations for One Quantitative Variable
- Summary Statistics for One Quantitative Variable
- The Investigative Question Revisited and Data Collection
- Random Sampling
- Experimental Design
On The Exam
20%–30% of Score
Unit 2: Probability, Random Variables, and Probability Distributions
You will build on understandings of simulated or empirical data distributions and fundamental principles of probability to represent, interpret, and calculate parameters for theoretical probability distributions for discrete random variables.
Topics may include:
- Estimating Probabilities Using Simulation
- Introduction to Probability
- Mutually Exclusive Events
- Conditional Probability
- Independent Events and Unions of Events
- Introduction to Random Variables and Probability Distributions
- The Binomial Distribution
- The Normal Distribution
On The Exam
15%–25% of Score
Unit 3: Inference for Categorical Data: Proportions
You will use statistical inference to construct and interpret confidence intervals to estimate population proportions and perform significance tests to evaluate claims about population proportions, provided that appropriate conditions are met.
Topics may include:
- Estimators
- Sampling Distributions for Sample Proportions
- Constructing a Confidence Interval for a Population Proportion
- Setting Up a Test for a Population Proportion
- Justifying a Claim Based on a Confidence Interval for the Difference Between Two Population Proportions
- Carrying Out a Test for the Difference Between Two Population Proportions
- Carrying Out a Chi-Square Test for Homogeneity or Independence
On The Exam
15%–25% of Score
Unit 4: Inference for Quantitative Data: Means
You will analyze quantitative data to make inferences about population means. You’ll discover how and why conditions for inference with proportions and means are similar and different.
Topics may include:
- Sampling Distributions for Sample Means
- Constructing a Confidence Interval for a Population Mean or Population Mean Difference
- Setting Up a Test for a Population Mean or Population Mean Difference
- Sampling Distributions for the Difference Between Two Sample Means
- Justifying a Claim Based on a Confidence Interval for the Difference Between Two Population Means
- Carrying Out a Test for the Difference Between Two Population Means
On The Exam
10%–20% of Score
Unit 5: Regression Analysis
You will explore relationships in two-variable quantitative data sets, assess correlation, and, if appropriate, use a linear model to predict values of the response variable from values of the explanatory variable.
Topics may include:
- Graphical Representations Between Two Quantitative Variables
- Correlation
- Linear Regression Models
- Least-Squares Regression
On The Exam
10%–20% of Score
Credit and Placement
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Course Resources
Link
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Download
AP Statistics Course and Exam Description
This is the core document for the course. It clearly lays out the course content and describes the exam and the AP Program in general.