Think Stats

Think Stats

Think Stats

  • Used Book in Good Condition

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—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you’ll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.

  • Develop your understanding of probability and statistics by writing and testing code
  • Run experiments to test statistical behavior, such as generating samples from several distributions
  • Use simulations to understand concepts that are hard to grasp mathematically
  • Learn topics not usually covered in an introductory course, such as Bayesian estimation
  • Import data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics tools
  • Use statistical inference to answer questions about real-world data

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3 comments

  1. 65 of 66 people found the following review helpful
    5.0 out of 5 stars
    Learning Statistics using Programming, August 11, 2011
    This review is from: Think Stats (Paperback)
    If your grasp of Programming exceeds your understanding of Basic Statistics, this book IS for you. As a University Statistics professor, I am constantly looking for reading materials that I can use to integrate Practical Statistics with programming. I am generally faced with the problem of having to mine Programming texts for Stats lessons, all too often I am faced with books that attempt to teach a programming language with examples from Freshman Statistics as an afterthought. (Too much of one, not enough of the other)

    This book comes at the problem from the other side. Given that you already have a healthy grasp on programming and are trying to learn Statistics, each topic is presented with helpful, real-world data examples, and a step-by-step explanation of how to code the solutions. That makes this book excellent supplementary material for a Statistics class, or at the very least, a wonderful refresher for those returning to Statistics, with programming in mind.

    Caution:
    This book is NOT for you if you do NOT have a basic understanding of Programming. This book will NOT teach you to program using statistics. It is meant to teach you statistics using programming.

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  2. 42 of 45 people found the following review helpful
    5.0 out of 5 stars
    100 pages and couple of hours to get a good flavor of Bayesian Stats, March 15, 2012
    By 
    Ravi Aranke (Hyderabad, India) –

    This review is from: Think Stats (Paperback)
    Bayesian statistics and Bayesian thinking has taken the world by storm. If you read Kahneman’s popular
    Thinking, Fast and Slow, you are advised to think in Bayesian terms viz. to adjust your prior beliefs in light of new evidence.

    However, there is a big gulf between knowing what you should do and actually being able to do Bayesian statistics in a mathematically correct way. The language of probability and ability to manipulate the algebra of probability statements is a prerequisite and that has some steep learning curve.

    Fortunately, thanks to Allen Downey, you are in luck if you know some python programming. (If not, just pick up a copy of Think Python: An Introduction to Software Design by the same author). The best part of this book is that is thin – running at just over 100 pages, you can work through it over a weekend. Better still, you can watch the author delivering an interactive seminar and just follow along. Search for ‘Bayesian statistics made (as) simple (as possible)’ on youtube.

    When he says that it is Bayesian Statistics made as simple as possible, that is no exaggeration.

    As some of the reviewers have mentioned, Allen Downey has kindly made this book, as well as few other books, freely available on his site. Hats off to you, Sir!

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  3. 24 of 25 people found the following review helpful
    4.0 out of 5 stars
    Good Book – Free from Authors Site, January 28, 2012
    By 
    Devin R (Pittsburgh, PA) –

    This review is from: Think Stats (Kindle Edition)
    This is a good book to teach programmers [python especially] how to use mathematical statistics in their programs. The only real shame about the Kindle version of this book is it is available for free under the creative commons from the publisher, Greenteapress, for free but it’s being sold here for a 10 spot.

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