Think Stats

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"O'Reilly Media, Inc.", Jul 1, 2011 - Computers - 138 pages
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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.

  • 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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Contents

Chapter 1 Statistical Thinking for Programmers
1
Chapter 2 Descriptive Statistics
11
Chapter 3 Cumulative Distribution Functions
23
Chapter 4 Continuous Distributions
33
Chapter 5 Probability
47
Chapter 6 Operations on Distributions
61
Chapter 7 Hypothesis Testing
73
Chapter 8 Estimation
85
Chapter 9 Correlation
97
Index
113
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About the author (2011)

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.

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