Statistics fundamentals

Over the course of my studies and especially my PhD, time and time again it proved necessary to refer back to the very basics of statistics. So here I’ve made a list of websites and tutorials that I found useful.

OnlineStatBook

One of the most useful resources has been this OnlineStatBook developed by Rice University, University of Houston Clear Lake, and Tufts University. It has very clear descriptions and insightful visualisations of a wide variety of subjects, including probability theory, means testing, regression, confidence intervals, Chi square tests and effect size calculations.

Points of significance

There is a wonderful series of articles in Nature Methods by Martin Krzywinski & Naomi Altman called “Points of Significance”. They describe statistical concepts in detail, ranging from error bars to machine learning. A non-exhaustive list with links to their articles is given here:

• error bars
• significance, P values and t-tests
• interpreting P values
• two factor designs
• linear regression
• logistic regression
• principal component analysis
• model selection and overfitting
• sampling distributions and bootstrap
• statistics versus machine learning