From pizza to the dark side of research. Image created with Dall·E 3 by the author.

Sneaky Science: Data Dredging Exposed

Delve into the motivations and consequences of p-hacking

A recent New Yorker headline reads, “They Studied Dishonesty. Was Their Work a Lie?”. What’s the story behind it? Behavioral economist Dan Ariely and behavioral scientist Francesca Gino, both acclaimed in their fields, are under scrutiny for alleged research misconduct. To put it bluntly, they’re accused of fabricating data to achieve statistically significant results.

Sadly, such instances are not rare. Scientific research has seen its share of fraud. The practice of p-hacking — e.g. manipulating data, halting experiments once a significant p-value is achieved, or only reporting significant findings — has long been a concern. In this article, we will reflect on why some researchers might be tempted to tweak their findings. We will show the consequences and explain what you can do to prevent p-hacking in your own experiments.

But before we get into the scandals and secrets, let’s start with the basics — a crash course in Hypothesis Testing 101. This knowledge will be helpful as we navigate the world of p-hacking.

Hypothesis Testing 101

Let’s recap the key concepts you need to know to fully grasp the post. If you are familiar with hypothesis testing, including the…