An Introduction to Statistics with Python With Applications in the Life Sciences /

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 cod...

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Main Author: Haslwanter, Thomas. (Author, http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Series:Statistics and Computing,
Subjects:
Online Access:https://doi.org/10.1007/978-3-319-28316-6
Table of Contents:
  • Part I: Python and Statistics
  • Why Statistics?
  • Python
  • Data Input
  • Display of Statistical Data
  • Part II: Distributions and Hypothesis Tests
  • Background
  • Distributions of One Variable
  • Hypothesis Tests
  • Tests of Means of Numerical Data
  • Tests on Categorical Data
  • Analysis of Survival Times
  • Part III: Statistical Modelling
  • Linear Regression Models
  • Multivariate Data Analysis
  • Tests on Discrete Data
  • Bayesian Statistics
  • Solutions
  • Glossary
  • Index.