When you search Google for an easy explanation of the Central Limit Theorem, the foundational theory in statistics, you find yourself frustrated, as normally the Web would tell you that
The central limit theorem (CLT) establishes that, in most situations, when independent random variables are added, their properly normalized sum tends toward a normal distribution (a bell curve) even if the original variables themselves are not normally distributed. From wikipedia
What exactly does that mean? Most of the people would not have a clue. But I found an intuitive tutorial of the Central Limit Theorem that explains what it is. This tutorial uses a visual style and animations, which guide learners step by step in understanding the theorem. Try yourself at http://mfviz.com/central-limit/.
(Screenshot of the animation in mfviz.com/central-limit/)