P-Hacking and Multiple Comparison Bias

Patrick David has a great article on hypothesis testing, p-hacking, and multiple comparison bias:

The most important part of hypothesis testing is being clear what question we are trying to answer. In our case we are asking:
“Could the most extreme value happen by chance?”
The most extreme value we define as the greatest absolute AMVR deviation from the mean. This question forms our null hypothesis.

Give this one a careful read and try out the code. This is an important topic for anyone who analyzes data to understand.

Related Posts

Naive Bays in R

Zulaikha Lateef takes us through the Naive Bayes algorithm and implementations in R: Naive Bayes is a Supervised Machine Learning algorithm based on the Bayes Theorem that is used to solve classification problems by following a probabilistic approach. It is based on the idea that the predictor variables in a Machine Learning model are independent of […]

Read More

Forensic Accounting: Cohort Analysis

I continue my series on forensic accounting techniques with cohort analysis: In the last post, we focused on high-level aggregates to gain a basic understanding of our data. We saw some suspicious results but couldn’t say much more than “This looks weird” due to our level of aggregation. In this post, I want to dig […]

Read More


January 2019
« Dec Feb »