An Introduction to Statistics with Python

With Applications in the Life Sciences

  • Thomas¬†Haslwanter

Part of the Statistics and Computing book series (SCO)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Python and Statistics

    1. Front Matter
      Pages 1-1
    2. Thomas Haslwanter
      Pages 3-4
    3. Thomas Haslwanter
      Pages 5-42
    4. Thomas Haslwanter
      Pages 43-49
    5. Thomas Haslwanter
      Pages 51-71
  3. Distributions and Hypothesis Tests

    1. Front Matter
      Pages 73-73
    2. Thomas Haslwanter
      Pages 75-88
    3. Thomas Haslwanter
      Pages 89-120
    4. Thomas Haslwanter
      Pages 121-137
    5. Thomas Haslwanter
      Pages 139-157
    6. Thomas Haslwanter
      Pages 159-173
    7. Thomas Haslwanter
      Pages 175-180
  4. Statistical Modeling

    1. Front Matter
      Pages 181-181
    2. Thomas Haslwanter
      Pages 183-220
    3. Thomas Haslwanter
      Pages 221-225
    4. Thomas Haslwanter
      Pages 227-236
    5. Thomas Haslwanter
      Pages 237-243
  5. Back Matter
    Pages 245-278

About this book

Introduction

This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis.     


Keywords

Python statistical tests applications in life sciences data analysis statistical methods programming statistics and computing alternative to R Python source code introductory statistics

Authors and affiliations

  • Thomas¬†Haslwanter
    • 1
  1. 1.School of Applied Health and Social SciencesUniversity of Applied Sciences Upper AustriaLinzAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-28316-6
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-28315-9
  • Online ISBN 978-3-319-28316-6
  • Series Print ISSN 1431-8784
  • Series Online ISSN 2197-1706
  • About this book
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