This paper is from Session 4D: Innovations in teaching statistics at the tertiary level

which comes under Topic 4: Statistics education at the post secondary (tertiary) level

Other papers under session 4D ... 4D1: Real-life module statistics: a happy Harvard experiment 4D2: Visualising inference 4D3: Enriching statistics courses with statistical diversions

(Monday 12th, 14:00-16:00)

Stats2: An applied statistics modeling course

Presenter

• Jeffrey Witmer (Oberlin College, United States)

Abstract

The typical Stats1 introductory course at the tertiary level covers one-sample and two-sample inference and ends with regression or perhaps one-way ANOVA. We propose that a second course in statistics be built around the idea of statistical modeling (“data = model + error”), beginning with a review of simple linear regression and continuing through two-way ANOVA and logistic regression. Unlike the situation in Stat1, students in Stat2 require access to powerful and flexible computing, which suggests that R be used to fit models. We discuss a Stat2 course that includes both traditional, normal-theory based, inference and randomization tests.

Other papers under session 4D ... 4D1: Real-life module statistics: a happy Harvard experiment 4D2: Visualising inference 4D3: Enriching statistics courses with statistical diversions