Lies, damned lies, and statistics

22nd April 2017 |   Professor Nick Lee

Lies and Statistics

Nick Lee on… Statistical significance testing

List time around, I explained the concept of endogeneity bias, and how it might influence how much trust you can have in the results of studies you see reported in the media, and also research projects and white papers you might read yourself. This time, I’m going to deal with the other major problem in drawing conclusions from research – that of tatistical significance testing.

Now, you might remember learning about statistical significance testing either at school, or university. It’s one of the foundational topics in any statistics, market research, psychology, or organizational research course. And now I’m going to tell you not to trust it? The short answer is yes, I am. The longer answer is that (like most things) it’s complicated.

When we use statistical significance testing for its correct purpose, it’s fine. However, most of the time we don’t. This has led to many problems, and a lot of the results of high-profile studies are not to be trusted because of this. In fact, in the psychological research fields, it is not overstating it to say that some academics are talking of a “crisis”, in part because of this issue.

Professor of Marketing at Warwick Business School | + posts

Nick Lee is Professor of Marketing at Warwick Business School and the Honorary Chair of Marketing and Organizational Research at Aston Business School. His research interests include sales management, social psychology, research methodology, and ethics. He is Editor in Chief of the European Journal of Marketing, the Section Editor for Sales Research Methods for the Journal of Personal Selling and Sales Management, and he serves on the review panel or editorial board of several other journals. Nick is an Honorary Fellow of the APS where he directs research activities. Contact: