Reading Scientific Data: Part 0

In this lesson, you’ll learn about how to read and critically assess scientific evidence, without needing to become a statistician. 

We’ll cover the basic vocabulary of statistics, including the difference between descriptive and inferential statistics, what a p-value and a confidence interval actually tell you (and don’t), why sample size and representativeness matter (especially in rare diseases) and how to spot the difference between correlation and causation. You’ll also look at how data visualisation can shape (or distort) the story a graph seems to tell. 

By the end, you’ll have a practical framework for reading a scientific paper or conference poster critically: what question was being asked, who was studied, how big and meaningful the results are, and what’s missing; so you can engage with evidence confidently in discussions with researchers, clinicians and regulators. 

This session is divided into four parts – watch them at your own time!