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Worked examples for exercises in Think Stats using the Scientific Python stack.

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Think Stats Exercises

This project contains my answers to exercises from the book Think Stats - Probability and Statistics for Programmers by Allen B Downey.

The book uses small Python programs to do simulations that provide intuitions to statistical concepts. The author builds up a small Python library that he uses throughout the book, almost like a Domain Specific Language (DSL).

Having used scientific Python (Numpy, Scipy, Matplotlib, Pandas) for a while now, I found the need to learn the DSL a bit of a pain, and decided to just use these libraries instead. Besides, I wanted to apply these ideas to my own projects without having to carry over or rebuild the core library, but rather to continue using the tools I am used to.

CAVEAT: the answers are not necessarily correct. I have tried to ensure that they are, but I am learning this stuff, so there might be errors in there, so please use at your own risk! If you do find errors please raise an issue, preferably telling me what I am doing wrong and the solution. I will update and give you credit on this page.

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Worked examples for exercises in Think Stats using the Scientific Python stack.

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