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Think Stats Probability and Statistics for Programmers Allen Downey

By: Contributor(s): Material type: TextTextSeries: Open textbook libraryDistributor: Minneapolis, MN Open Textbook LibraryPublisher: [Place of publication not identified] Green Tea Press [2014]Copyright date: ©2014Edition: 2eDescription: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781491907337
Subject(s): LOC classification:
  • QA76
Online resources:
Contents:
Preface -- 1 Exploratory data analysis -- 2 Distributions -- 3 Probability mass functions -- 4 Cumulative distribution functions -- 5 Modeling distributions -- 6 Probability density functions -- 7 Relationships between variables -- 8 Estimation -- 9 Hypothesis testing -- 10 Linear least squares -- 11 Regression -- 12 Time series analysis -- 13 Survival analysis -- 14 Analytic methods
Subject: Think Stats is an introduction to Probability and Statistics for Python programmers. Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets. If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.
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Preface -- 1 Exploratory data analysis -- 2 Distributions -- 3 Probability mass functions -- 4 Cumulative distribution functions -- 5 Modeling distributions -- 6 Probability density functions -- 7 Relationships between variables -- 8 Estimation -- 9 Hypothesis testing -- 10 Linear least squares -- 11 Regression -- 12 Time series analysis -- 13 Survival analysis -- 14 Analytic methods

Think Stats is an introduction to Probability and Statistics for Python programmers. Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets. If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.

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In English.

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