An Introduction to Statistics with Python: With Applications in the Life Sciences
暫譯: 使用 Python 的統計學入門：生命科學中的應用

Haslwanter, Thomas

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

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商品描述

Now in its second edition, this textbook provides an introduction to 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.

For this new edition, the introductory chapters on Python, data input and visualization have been reworked and updated. The chapter on experimental design has been expanded, and programs for the determination of confidence intervals commonly used in quality control have been introduced. The book also features a new chapter on finding patterns in data, including time series. A new appendix describes useful programming tools, such as testing tools, code repositories, and GUIs.

The provided working code for Python solutions, together with easy-to-follow examples, will reinforce the reader's immediate understanding of the topic. Accompanying data sets and Python programs are also available online. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis.

 

With examples drawn mainly from the life and medical sciences, this book is intended primarily for masters and PhD students. As it provides the required statistics background, the book can also be used by anyone who wants to perform a statistical data analysis.

 

 

 

商品描述(中文翻譯)

現在已經進入第二版，本教科書提供了對 Python 及其在統計數據分析中應用的介紹。內容涵蓋了連續、離散和類別數據的常見統計檢定，以及線性回歸分析、存活分析和貝葉斯統計的主題。

在這一新版中，關於 Python、數據輸入和可視化的入門章節已經重新編寫和更新。實驗設計的章節也有所擴展，並引入了在質量控制中常用的置信區間計算程序。本書還新增了一章，專門探討數據中的模式發現，包括時間序列。新的附錄描述了一些有用的編程工具，如測試工具、代碼庫和圖形用戶界面（GUI）。

提供的 Python 解決方案的工作代碼，以及易於跟隨的範例，將加強讀者對主題的即時理解。隨附的數據集和 Python 程序也可在線獲得。隨著 Python 生態系統的最新進展，Python 已成為科學計算的熱門語言，為統計數據分析提供了強大的環境。

本書主要以生命科學和醫學科學中的範例為主，主要針對碩士和博士生。由於提供了所需的統計背景，本書也適合任何希望進行統計數據分析的人士使用。

作者簡介

Thomas Haslwanter is a Professor at the School of Medical Engineering and Applied Social Sciences at 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 Tübingen, 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 15 years.

 

 

作者簡介(中文翻譯)

托馬斯·哈斯瓦特是奧地利上奧地利應用科技大學醫療工程與應用社會科學學院的教授，同時也是瑞士蘇黎世聯邦理工學院的講師。他曾在澳大利亞悉尼大學和德國圖賓根大學擔任研究員。他在醫學研究方面擁有豐富的經驗，專注於眩暈和頭暈的診斷與治療以及康復。經過15年的廣泛使用Matlab後，他發現了Python，現在用於統計數據分析、聲音和影像處理以及生物模擬應用。他在學術環境中教學已超過15年。

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