This paper is from Session 4F: Opening up the data world wider and faster

which comes under Topic 4: Statistics education at the post-secondary level

Introductory statistics in the 21st century

Presenter

• Richard De Veaux (Williams College, United States)

Abstract

Big data is everywhere. Companies, governments and the media can’t seem to get enough of the data deluge and the tsunami of data that is about to overwhelm us and/or make us a smarter planet. But, what’s the connection between the Statistics taught in an introductory statistics course and the statistical analyses that are performed throughout the world every day? How close is this version of Statistics to real world practice?

Most courses in Statistics now start with exploratory data analysis, move on to probability and then inference. If time permits, they include models, often ending at simple regression. Unfortunately, models are the most important topic, and comprise the core of modern big data analytics. Maybe we’re teaching the course backward. We’ll describe an approach that starts the course with models, making full use of students’ intuition about the world and exposing them early to the power of statistical models