Exploring one-variable data
14 lessonsDescribing one variable with displays, center, spread and position, comparing groups, and the normal model, taught again at AP depth.
Exploring two-variable data
14 lessonsTwo-way tables and scatter plots taught again, then correlation, the least squares line, residuals, r squared, influential points and transformations to linearity.
Collecting data: sampling and experiments
10 lessonsHow the way data are gathered decides what can be concluded, from random sampling designs to randomized experiments.
Probability and random variables
13 lessonsThe probability rules taught again, then random variables, with their distributions, means, spreads and the rules for combining them.
Binomial and geometric distributions
6 lessonsTwo families of counts from repeated independent trials, their formulas, means and spreads, and when a binomial looks normal.
Sampling distributions
6 lessonsHow a statistic varies from sample to sample, and why sample proportions and means are close to normal.
Inference for proportions: confidence intervals
7 lessonsEstimating one proportion, or the difference of two, with an interval, and what the confidence level does and does not promise.
Inference for proportions: significance tests
10 lessonsTesting a claim about one or two proportions, reading a p-value, and the errors and power of a test.
Inference for means
7 lessonsIntervals and tests for one mean, two means and paired data, using the t distribution.
Chi-square tests
3 lessonsTesting whether counts fit a model, and whether two categorical variables are related.
Inference for slopes
5 lessonsWhether a sample regression line shows a real linear relationship, and choosing the right procedure for any question.