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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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Detalles Bibliográficos
Autor principal: Haslwanter, Thomas
Lenguaje:eng
Publicado: Springer 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-28316-6
http://cds.cern.ch/record/2205665
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author Haslwanter, Thomas
author_facet Haslwanter, Thomas
author_sort Haslwanter, Thomas
collection CERN
description 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. .
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spelling cern-22056652021-04-21T19:33:29Zdoi:10.1007/978-3-319-28316-6http://cds.cern.ch/record/2205665engHaslwanter, ThomasAn introduction to statistics with Python: with applications in the life sciencesMathematical Physics and MathematicsThis 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. .Springeroai:cds.cern.ch:22056652016
spellingShingle Mathematical Physics and Mathematics
Haslwanter, Thomas
An introduction to statistics with Python: with applications in the life sciences
title An introduction to statistics with Python: with applications in the life sciences
title_full An introduction to statistics with Python: with applications in the life sciences
title_fullStr An introduction to statistics with Python: with applications in the life sciences
title_full_unstemmed An introduction to statistics with Python: with applications in the life sciences
title_short An introduction to statistics with Python: with applications in the life sciences
title_sort introduction to statistics with python: with applications in the life sciences
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-28316-6
http://cds.cern.ch/record/2205665
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