# Your AP Statistics Resource Center

## Overview of AP Statistics

AP Statistics stands for Advanced Placement Statistics. It is a college-level course offered by the College Board to high school students who are interested in studying statistics at an advanced level. The course covers a wide range of topics, including data analysis, sampling, experimentation, and inference. The course is rigorous and requires students to have a good grasp of algebra. It expects them to engage in data collection, statistical analysis, and interpretation of results, as well as to showcase their understanding of probability and inferential reasoning.

## Course content

Unit 2: Exploring Two-Variable Data

You’ll build on what you’ve learned by representing two-variable data, comparing distributions, describing relationships between variables, and using models to make predictions.

- Comparing representations of 2 categorical variables
- Calculating statistics for 2 categorical variables
- Representing bivariate quantitative data using scatter plots
- Describing associations in bivariate data and interpreting correlation
- Linear regression models
- Residuals and residual plots
- Departures from linearity

Unit 3: Collecting Data

You’ll be introduced to study design, including the importance of randomization. You’ll understand how to interpret the results of well-designed studies to draw appropriate conclusions and generalizations.

- Planning a study
- Sampling methods
- Sources of bias in sampling methods
- Designing an experiment
- Interpreting the results of an experiment

Unit 4: Probability, Random Variables, and Probability Distributions

You’ll learn the fundamentals of probability and be introduced to the probability distributions that are the basis for statistical inference.

- Using simulation to estimate probabilities
- Calculating the probability of a random event
- Random variables and probability distributions
- The binomial distribution
- The geometric distribution

Unit 5: Sampling Distributions

As you build understanding of sampling distributions, you’ll lay the foundation for estimating characteristics of a population and quantifying confidence.

- Variation in statistics for samples collected from the same population
- The central limit theorem
- Biased and unbiased point estimates
- Sampling distributions for sample proportions
- Sampling distributions for sample means

Unit 6: Inference for Categorical Data: Proportions

You’ll learn inference procedures for proportions of a categorical variable, building a foundation of understanding of statistical inference, a concept you’ll continue to explore throughout the course.

- Constructing and interpreting a confidence interval for a population proportion
- Setting up and carrying out a test for a population proportion
- Interpreting a p-value and justifying a claim about a population proportion
- Type I and Type II errors in significance testing
- Confidence intervals and tests for the difference of 2 proportions

Unit 7: Inference for Quantitative Data: Means

Building on lessons learned about inference in Unit 6, you’ll learn to analyze quantitative data to make inferences about population means.

- Constructing and interpreting a confidence interval for a population mean
- Setting up and carrying out a test for a population mean
- Interpreting a p-value and justifying a claim about a population mean
- Confidence intervals and tests for the difference of 2 population means

Unit 8: Inference for Categorical Data: Chi-Square

You’ll learn about chi-square tests, which can be used when there are two or more categorical variables.

- The chi-square test for goodness of fit
- The chi-square test for homogeneity
- The chi-square test for independence
- Selecting an appropriate inference procedure for categorical data

Unit 9: Inference for Quantitative Data: Slopes

You’ll understand that the slope of a regression model is not necessarily the true slope but is based on a single sample from a sampling distribution, and you’ll learn how to construct confidence intervals and perform significance tests for this slope.

- Confidence intervals for the slope of a regression model
- Setting up and carrying out a test for the slope of a regression model
- Selecting an appropriate inference procedure

## Exam Date

### AP Statistics Exam

Will be conducted on

##### Tue, May 7, 2024 | 12 PM Local

## AP Statistics Exam Guide

Are you struggling with the AP Statistics exam? or just need some additional help with data analysis, probability, statistical inference, and regression analysis. Learning these complex concepts can be often difficult to self-study. The AP Statistics course is rated as moderately easy with a rating of 4.8 out of 10 in difficulty by class alumnae. It has a large enrollment and 95% of students recommend it, the passing rate for 2022 was 60%. Our AP Statistics Exam Guide here will cover everything, including creating a study plan, comprehending difficult statistical concepts, and making the most of useful resources. So, let’s get started and prepare to ace the AP Statistics exam!

## Explore more in AP Statistics

## AP Statistics Course Resources

## AP Statistics Course

The College Board website offers a variety of extra resources to help AP Statistics students succeed on the exam. These resources include the AP Statistics Course at a Glance, the AP Statistics Course and Exam Description, the AP Statistics CED Scoring Guidelines, and more. To help students prepare for the AP Statistics exam, we have provided links to these extra resources below.

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