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

Chapter 1 Exploratory Data Analysis
1
Chapter 2 Distributions
15
Chapter 3 Probability Mass Functions
27
Chapter 4 Cumulative Distribution Functions
39
Chapter 5 Modeling Distributions
49
Chapter 6 Probability Density Functions
65
Chapter 7 Relationships Between Variables
79
Chapter 8 Estimation
91
Chapter 10 Linear Least Squares
117
Chapter 11 Regression
129
Chapter 12 Time Series Analysis
145
Chapter 13 Survival Analysis
165
Chapter 14 Analytic Methods
183
Index
197
About the Author
207
Copyright

Chapter 9 Hypothesis Testing
101

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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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