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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—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.
Allen Downey is an Associate Professor of Computer Science at the Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master’s and Bachelor’s degrees from MIT.
Preface
Chapter 1: Statistical Thinking for Programmers
Chapter 2: Descriptive Statistics
Chapter 3: Cumulative Distribution Functions
Chapter 4: Continuous Distributions
Chapter 5: Probability
Chapter 6: Operations on Distributions
Chapter 7: Hypothesis Testing
Chapter 8: Estimation
Chapter 9: Correlation
Colophon
Anonymous
Posted Sun Mar 30 00:00:00 EDT 2014
Full of good things
Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.Anonymous
Posted Thu Jul 12 00:00:00 EDT 2012
"Yes. Icepool and Tigerheart are my sister's kits."
Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.CromsFury
Posted Thu Aug 11 00:00:00 EDT 2011
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.
Was this review helpful? Yes NoThank you for your feedback. Report this reviewThank you, this review has been flagged.Anonymous
Posted Sat Sep 10 00:00:00 EDT 2011
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Overview
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,...