In the early 20 th century, Guinness breweries in Dublin had a policy of hiring the best graduates from Oxford and Cambridge to improve their industrial processes. At the time, it was considered a ...

Having data is only half the battle. How do you know your data actually means something? With some simple Python code, you can quickly check if differences in data are actually significant. In ...

In the realm of technical product development, hypothesis testing acts as a bridge between design, data and decision-making. It enables teams to move beyond assumptions and validate their ideas ...

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is most often used by researchers to test predictions, called hypotheses. The first step in ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

It can be difficult to know what analysis to perform on your dataset. This page is designed to help you. Finally, you will need to know about some specific analyses, what they are designed to do and ...

Explore essential statistical strategies for accurate protein quantification and differential expression analysis.

Post-hoc testing is carried out after a statistical analysis where you have performed multiple significance tests, ‘post-hoc’ coming from the Latin “after this”. Post-hoc analysis represents a way to ...

Learn about t-test assumption, including scale, sampling, normality, sample size, and variance equality, for accurate statistical analysis and reliable results.