Conditional Probability

Introducing conditional probability and independence of events. Bayes' rule comes in as well.

Basic Concepts

Introducing the concept of the probability of an event. Also covers set operations and the sample-point method.

Definitions for Continuous Random Variables

The probability density function, cumulative distribution function, expectation and variance for a continuous random variable.

Density Estimation

Wanna know more about histograms and density plots?

Bootstrap

The procedure and applications of the nonparametric bootstrap.

Categorical Data

Dealing with contingency tables. Fisher's exact test comes back, together with Chi-squared test and likelihood-ratio test. We also talk about testing goodness-of-fit.

Correlation and Concordance

Measures for the strength of relationships between variables (two or more). The Spearman rank correlation coefficient, Kendall's tau and Kendall's W are introduced.

Basic Tests for Three or More Samples

Nonparametric analogues of the one-way classification ANOVA and the simplest two-way classifications, namely the Kruskal-Wallis test, the Jonckheere-Terpstra test, and the Friedman test.

Two Independent Samples

With two independent samples, we may ask about the centrality of the population distribution and see if there's a shift. Wilcoxon-Mann-Whitney is here!

Methods for Paired Samples

An obvious extension of the one-sample procedures.