Here are some educational articles on statistics.
More articles and data visualizations coming soon!

The Central Limit Theorem  Introduction, Intuition and Proof
All about the Central Limit Theorem (CLT), including:
 An introduction explaining what the central limit theorem is and why it is useful.
 An intuitive explanation of why the central limit makes sense, by visualizing convolutions of discrete random variables.
 A proof of the central limit theorem using the method of Fourier transforms.

The Central Limit Theorem  Introduction with Simulations and Examples
Interactive simulations and practical examples to help you understand the meaning of the central limit theorem for the sampling distribution of sample means. Also includes a discussion of the effect of sample size on the central limit theorem, the minimum sample size, and what happens for sample sizes less than 30.

Where does the normal distribution graph get its "bellcurve" shape?
Intuitive explanation for the shape of the normal / Gaussian distribution. We start by calculating the probability distributions for the outcomes from dice rolls, then extend this to the sum of randomly selected real numbers. There are graphics and animations to help demonstrate how the bell curve naturally arises in these situations.