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Introduction Statistics Python Applications Life by Haslwanter Thomas (35 results)
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Condition: good. Fast Free Shipping â" Good condition. It may show normal signs of use, such as light writing, highlighting, or library markings, but all pages are intact and the book is fully readable. A solid, complete copy that's ready to enjoy.
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Hardcover. 9.5x6", xvii+278 pp. VG, clean & tight.
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An Introduction to Statistics with Python: With Applications in the Life Sciences (Statistics and Computing)
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hardcover. Condition: New. 2nd ed. 2022. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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An Introduction to Statistics with Python: With Applications in the Life Sciences (Statistics and Computing)
Book 32 of 37: Statistics and ComputingSeller: Ria Christie Collections, Uxbridge, United Kingdom
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An Introduction to Statistics with Python : With Applications in the Life Sciences
Book 32 of 37: Statistics and ComputingUS$ 66.03
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Introduction to Statistics With Python : With Applications in the Life Sciences
Book 32 of 37: Statistics and ComputingSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Introduction to Statistics With Python : With Applications in the Life Sciences
Book 32 of 37: Statistics and ComputingSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Introduction to Statistics With Python : With Applications in the Life Sciences
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An Introduction to Statistics with Python: With Applications in the Life Sciences (Statistics and Computing)
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Introduction to Statistics With Python : With Applications in the Life Sciences
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An Introduction to Statistics with Python : With Applications in the Life Sciences
Book 32 of 37: Statistics and ComputingLanguage: English
Published by Springer, Palgrave Macmillan, 2018
ISBN 10: 3319803239 ISBN 13: 9783319803234
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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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