AP Statistics: Comprehensive Exam Review

This intensive AP Statistics review course provides students with the tools and strategies needed to excel on the exam, with emphasis on calculator proficiency. Students will master key statistical concepts and methodologies, develop problem-solving skills, and gain confidence in tackling both multiple-choice and free-response questions. By the end of this course, you'll be equipped to confidently approach the AP Statistics exam and achieve your target score.

Exploring Data Analysis

• Describing and comparing distributions of single-variable data — including measures of center, spread, shape, and outliers
• Analyzing and interpreting graphical displays — histograms, boxplots, scatterplots, and other visualizations
• Summarizing categorical data using tables and charts — understanding marginal and conditional distributions

Two-Variable Data

• Examining relationships between two categorical variables — using two-way tables to calculate conditional probabilities
• Modeling relationships between two quantitative variables — least squares regression, correlation, and interpreting residuals
• Assessing the fit of a linear model — evaluating residual plots and correlation coefficients

Probability

• Understanding basic probability rules — including the addition, multiplication, and complement rules
• Calculating conditional probabilities — using Bayes' Theorem to solve for conditional probabilities
• Working with independent and dependent events — determining the probability of events occurring together or separately

Random Variables and Probability Distributions

• Defining and working with discrete and continuous random variables
• Calculating expected values and standard deviations of random variables
• Applying the properties of binomial and geometric distributions — calculating probabilities and expected values

Sampling Distributions

• Understanding the concept of a sampling distribution — and its properties
• Applying the central limit theorem — for sample means and sample proportions
• Calculating probabilities related to sample means and proportions

Inference for Means and Proportions

• Constructing and interpreting confidence intervals — for means and proportions
• Performing hypothesis tests — for means and proportions
• Understanding Type I and Type II errors — and their implications in hypothesis testing

Experimental Design

• Identifying sources of bias in sampling and experimentation
• Designing experiments — including control groups, randomization, and replication
• Analyzing data from experiments — to draw valid conclusions

Investigative Tasks and Complex Problem Solving

• Applying statistical concepts to novel situations — interpreting and synthesizing information from multiple units
• Developing problem-solving strategies — for tackling challenging and unfamiliar questions
• Effectively communicating statistical results — in written and oral formats