A comprehensive textbook on statistics written for both novices and advanced analysts. This - one of a kind - book offers a comprehensive, almost encyclopedic presentation of statistical methods and analytic approaches used in science, industry, business, and data mining, written from the perspective of the real-life practitioner ('consumer') of these methods. The primary emphasis is on applications rather than theoretical derivations and formulas. The authors, experienced researchers, draw on their diverse experiences as teachers of quantitative methods at the graduate and undergraduate levels with extensive, real-life consulting expertise (they have been involved in hundreds of projects in various areas of science, business, and industry, on all continents).
History of this book. The earlier editions of this unique book were available for over 10 years on the Internet, where it has earned praise from thousands of readers and benefited from their comments, questions, and requests for coverage of specific topics. The electronic version of this textbook has also won the prestigious distinction of becoming the only Internet resource on statistics and data analysis recommended by Encyclopedia Britannica.
From a 'Novice' to Advanced Analyst. This book was written without assuming that the reader has any prior knowledge of statistics. Instead, it successfully guides the reader all the way from the basic foundations of statistical reasoning, to the most advanced, cutting-edge methods. It includes hundreds of examples and thousands of illustrations created with leading edge data visualization and data mining software. This unusually comprehensive book includes also chapters on industrial statistics, on the emerging areas of predictive analytics, data mining and text mining, and a 200-page, illustrated Glossary of statistical terms.
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Why I wrote this book Think Stats: Probability and Statistics for Programmers is a textbook for a new. • Since I am making this book available under a free license, I wanted to.
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- An Introduction to Statistics with Python Book Description: 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.
- Norman Matloff has written a mathematical statistics textbook for computer science students that's free. Kind of a niche market, I suppose. For what it's worth, I haven't read it, but Matloff has a Ph.D. In mathematical statistics, works for a computer science department, and wrote a really good R book, that I recommend for people who want to go to the next stage of programming R better (as.