作者简介

Thomas Haslwanter is a Professor at the Department of Medical Engineering of the University of Applied Sciences Upper Austria in Linz, and lecturer at the ETH Zurich in Switzerland. He also worked as a researcher at the University of Sydney, Australia and the University of Tuebingen, Germany. He has extensive experience in medical research, with a focus on the diagnosis and treatment of vertigo and dizziness and on rehabilitation. After 15 years of extensive use of Matlab, he discovered Python, which he now uses for statistical data analysis, sound and image processing, and for biological simulation applications. He has been teaching in an academic environment for more than 10 years.

内容简介

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.


Thomas Haslwanter is a Professor at the Department of Medical Engineering of the University of Applied Sciences Upper Austria in Linz, and lecturer at the ETH Zurich in Switzerland. He also worked as a researcher at the University of Sydney, Australia and the University of Tuebingen, Germany. He has extensive experience in medical research, with a focus on the diagnosis and tre...

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豆瓣评论

  • iphyer
    还行,写得偏简单,不过按照 Bio 同学的基础来说是很合适的04-17
  • 躺学再分析
    内容涉及的广,但是你要说是入门,那我吊死~10-31
  • 整体还可以,内容比较全面,专门有讲解一些函数的结果是怎么算出来的。但部分内容只是随便一提,需要自己再仔细研究。本书代码是Python3版本12-06

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