Introduction to Statistical tests

Objectives

Understanding of how a test is built and what is at stake in its implementation.

Knowledge of classical tests and their application framework.

Assimilation of theoretical notions on parametric tests

Course outline

Introduction to hypothesis testing theory: decision rule, rejection zone, 1st and 2nd species error, p-value

Common tests: likelihood ratio (simple and generalized), parametric (mean, proportion, variance), non-parametric (chi-square, Kolmogorov-Smirnov, ranks).

Population comparisons, ANOVA

Tests for linear and logistic regression.

Prerequisites

Integration and Probability, Inferential Statistics