Think Stats: Exploratory Data Analysis

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"O'Reilly Media, Inc.", Oct 16, 2014 - Computers - 226 pages

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

By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts.

New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries.

  • Develop an 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
  • Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools
  • Use statistical inference to answer questions about real-world data
 

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Contents

Section 1
Section 2
Section 3
Section 4
Section 5
Section 6
Section 7
Section 8
Section 21
Section 22
Section 23
Section 24
Section 25
Section 26
Section 27
Section 28

Section 9
Section 10
Section 11
Section 12
Section 13
Section 14
Section 15
Section 16
Section 17
Section 18
Section 19
Section 20
Section 29
Section 30
Section 31
Section 32
Section 33
Section 34
Section 35
Section 36
Section 37
Section 38
Section 39

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About the author (2014)

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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