I have been teaching a course called Sports Economics for over 15 years, meaning that I am old. In the teaching of this course, I require the students to read a plethora of peer-reviewed economic research that employs statistical analysis. Each semester I take a full class period to review a topic called linear multivariate regression and then build on that as the semester moves forward, with the realization that my Sports Economics course is NOT a course on statistics but uses and analyzes a plethora of statistical concepts. As a help, I have decided to include some links on statistics that occur in Sports Economics.

First, the course is based on regression analysis using the subject called econometrics. Here is a great piece by Thoma on in how economists use econometrics and why. Once a statistical analysis has been performed, Stevenson and Wolfers explain what should you be looking for in terms of the big picture as to whether this is important or even interesting.

In terms of tying some of this statistical terminology to everyday thinking, here are some helps:

The difference between Type I errors (false positive) and Type II errors (false negative).

Examples of spurious correlations (i.e. variables that are correlated, but have nothing to do with each other).

A nice critique of only using p values in statistical analysis.

How some state insignificant (p-value) results.

Using dance to explain some statistical concepts.

## Tuesday, August 26, 2014

Subscribe to:
Post Comments (Atom)

## No comments:

Post a Comment