**Central Limit Theorem **We will make some observations and do some experiments first. At the end we can summarize the understanding and it will become a definition/explanation.Let us say we have a dice and the sample space ( or a set of all the possibilities) for a roll is {1, 2, 3, 4, 5, 6}.Let us pick a random number from this set, or if you have a dice, roll it. Let us say I rolled it and got a number say 6. Let us roll it a 100 times. Since it is difficult to roll it that many times, we will use computer to do it.

**Statistical Distribution Functions **This post is mainly about observing the theoretical distributions with variation of the terms that make the equations. There will be a lot of animations which will hopefully help improve your understanding of these concepts.

1.Normal Distribution

2.Exponential Distribution

3.Gamma Distribution

4.Weibull Distribution

**Pearson Correalation **In this page we will look at concepts about Pearson Correlation. Pearson correlation a way to estimate the strength of the Linear correlation between two variables of which one is dependent and the other is independent. Let us start by looking at a scatter plot.

**One Way Analysis of Variances (ANOVA) – A visual guide **In this post, we will learn about the ANOVA and also visualize the data alongside. We will be mostly learning it in Mathematica. Like always, I will try to present with many visual elements.

**MRG32k3a **This is a random number generator developed by Pierre L’Ecuyer. The link to the original text can be found here http://simul.iro.umontreal.ca/rng/MRG32k3a.c . I have coded two different versions of MRG32k3a.

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