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# Think Stats

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If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.

You'll work with a case study throughout the book to help you learn the entire data analysis process—fr ...more

You'll work with a case study throughout the book to help you learn the entire data analysis process—fr ...more

## Get A Copy

Paperback, 138 pages

Published
July 22nd 2011
by O'Reilly Media
(first published January 1st 2011)

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Oct 22, 2019
Nathan Brodsky
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The book is full of valuable insights and good, elaborate explanations. Well worth the read.

For starters, it doesn't actually list what a student should know ahead ...more

One annoyance. I think I'm maybe the perfect audience for this book: someone who took stats long ago, has worked with data ever since in some capacity, but has moved further and further away from the first principles/fundamentals. Someone who speaks Python and wants to port all of her Stata skillz onto pandas (the Python lib ...more

Free online version: https://greenteapress.com/wp/think-st...
...more

Now, that's a more severe judgment than I intend because there were parts of this book that were helpful and deepened my understanding.

In most stats books, I find it difficult to separate the material that explains the stats concepts from the material (if any - since this is always under-represented) that explains how to do stats (i.e. how to analyse a dataset or how to analyse the results of an experiment). This book is no ...more

Much of my frustration with this book can be summed by an example glossary entry: "chi-squared test: A test that uses the chi ...more

A lot of the actual python code has been abstracted by the author and put in classes and functions, making the examples easy to replicat ...more

The nice thing about it is that you go through the same prolems/datasets from one chapter to another. And you build on top of what you learned in a very cohe ...more

My primary gripe is that the code snippets frequently use functions that are unexplained before they are used, or IMO unnecessarily introduce the use of OOP, which only makes following along more difficult.

Formatting-wise, I think the book would also benefit from adding syntax highlighting (unless that was just SafariBooks), PEP8 compliant function naming, and the flavor ...more

Although it is a good beginner level book for practical statistics, the author uses too many "thinkplot" libraries every now and then to explain the concepts. It made it a lot harder to interpret the actual real-life implementation of those functions since I have worked with Pandas, Numpy and Matplotlib libraries before. It'd have been better if the examples used raw Python code used in actual data science applications.

*This review has been hidden because it contains spoilers. To view it, click here.*

Also somewhat unconventional selection & sequencing of topics, as well as some atypical emphases (e.g. Cumulative Distribution Functions) for a Stats 101 program. This makes it a nice complement to traditional materials. Not sure how ef ...more

*This review has been hidden because it contains spoilers. To view it, click here.*

You need to know Python to get the most out of this book, which really wasn't a problem for me. All code is available online and well-commented. Maybe not the best coding style, but hey he's a professor. What do you expect?

There is a bit of calculus, but it's mainly using the notation to get a concept across. Nothing to sweat over. (Do the ...more

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Allen Downey is a professor of Computer Science at Olin College and the author of a series of open-source textbooks related to software and data science, including Think Python, Think Bayes, and Think Complexity, which are also published by O’Reilly Media. His blog, Probably Overthinking It, features articles on Bayesian probability and statistics. He holds a Ph.D. in computer science from U.C. Be
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