AP Statistics Lectures

by Arnold Kling

Summary and Study Outline for AP Statistics

This page summarizes what you have to study for the AP. It links back to earlier lectures. There are four main topics for the AP--descriptive statistics, experimental design, probability, and statistical inference.

Descriptive Statistics

Be able to define standard deviation, variance, mean, median, quartile, interquartile range, outlier, skewed left, skewed right. Consider a boxplot, a stemplot, a histogram, or a scatterplot. Be able to state whether each of these is useful for assessing whether data are normal or skewed, assessing whether a bivariate relationship is linear or nonlinear, comparing two distributions, or showing outliers.

Experimental Design

Know how to do a simulation (such as our simulation of the NCAA brackets). Explain how an experiment is better than an observational study for showing causality. Be able to define and give examples of a lurking variable, a confounding variable, blind experiment, double-blind experiment, and blocking.

Probability

Understand the concepts of expected value, Failure Models (how the probability of a kipa falling off depends on the number of clips), Contingency tables and conditional probability, the binomial distribution and the geometric distribution.

Useful practice problems are:

- basic probability
- more basic probability
- expected value, binomial, geometric
- review of expected value, binomial, geometric
- more review
- cumulative review, problems 1-7

Statistical Inference

Be familiar with working with the normal distribution and with the terminology of statistical inference. (confidence interval, type I and type II error, etc.).

Understand when to use a Z-test, when to use the different t-tests (ordinary, matched-pairs, and two-sample), when to use one-sided or two-sided alternative.

Know when and how to use Chi-square tests. Know the basic formulas for regression, and be able to interpret regression output.

Useful practice problems are: