{"product_id":"an-introduction-to-statistics-with-python-with-applications-in-the-life-sciences-hardcover","title":"An Introduction to Statistics with Python: With Applications in the Life Sciences - Hardcover","description":"\u003cp\u003eby \u003cb\u003eThomas Haslwanter\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eNow 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.\u003c\/p\u003e\u003cp\u003eFor 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.\u003c\/p\u003eThe 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.\u003cp\u003e\u003c\/p\u003e\u003cp\u003eWith 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. \u003c\/p\u003e\u003cbr\u003e\u003cp\u003e\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eNow 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.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eFor 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.\u003c\/p\u003eThe 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.\u003cp\u003e\u003c\/p\u003e\u003cp\u003eWith 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. \u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eThomas Haslwanter\u003c\/b\u003e 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.\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 336\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.81 x 9.21 x 6.14 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e November 16, 2022\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42739871252543,"sku":"9783030973704","price":194.38,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/140909553dc88d23b8bd1b08721dab42.webp?v=1765158098","url":"https:\/\/dhlswag.com\/products\/an-introduction-to-statistics-with-python-with-applications-in-the-life-sciences-hardcover","provider":"BBB","version":"1.0","type":"link"}