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An Introduction To Statistics With Python: With Applications In The Life Sciences (Statistics And Computing)

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.     

Series: Statistics and Computing

Hardcover: 278 pages

Publisher: Springer; 1st ed. 2016 edition (July 21, 2016)

Language: English

ISBN-10: 3319283154

ISBN-13: 978-3319283159

Product Dimensions: 6.1 x 0.7 x 9.2 inches

Shipping Weight: 1.7 pounds (View shipping rates and policies)

Average Customer Review: 3.5 out of 5 stars  See all reviews (2 customer reviews)

Best Sellers Rank: #345,943 in Books (See Top 100 in Books) #58 in Books > Computers & Technology > Programming > Languages & Tools > Compilers #69 in Books > Textbooks > Medicine & Health Sciences > Research > Biostatistics #127 in Books > Medical Books > Basic Sciences > Biostatistics

Dr Haslwanter was kind enough to provide me with an early copy of his book, which I found to be immensely helpful. The book provides a great overview of Python tools for hypothesis testing, probability distributions, common statistical tests, and statistical modeling. It even includes a chapter on Bayesian analysis! The book provide elegant code that applies the statistical methods to scenarios in the biological sciences which I found especially helpful. It is a very thoughtful and well written book, and fills a needed gap in the scientific python literature.

Good content, but the "Kindle" version is nothing more than a PDF file. Very disappointed!

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