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 Title Introduction to Statistical Thought
 Author(s) Michael Lavine
 Publisher: Orange Grove Texts Plus (September 24, 2009); eBook (Updated, February 21, 2013)
 License(s) CC BYNCSA 3.0 US
 Paperback 434 pages
 eBook PDF, 475 page, 40.1 MB
 Languages: English, Belorussian, Polish
 ISBN10: 1616100486
 ISBN13: 9781616100483
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Book Description
The book is intended as an upper level undergraduate or introductory graduate textbook in statistical thinking with a likelihood emphasis for students with a good knowledge of calculus and the ability to think abstractly. By "statistical thinking" is meant a focus on ideas that statisticians care about as opposed to technical details of how to put those ideas into practice. The book does contain technical details, but they are not the focus. By "likelihood emphasis" is meant that the likelihood function and likelihood principle are unifying ideas throughout the text.
Another unusual aspect is the use of statistical software as a pedagogical tool. That is, instead of viewing the computer merely as a convenient and accurate calculating device, the book uses computer calculation and simulation as another way of explaining and helping readers understand the underlying concepts.
The book is written with the statistical language R embedded throughout.
About the Authors Michael Lavine is a Professor of Statistics at University of Massachusetts Amherst.
 Statistics, Mathematical Statistics, and SAS Programming
 The R Programming Language
 Probability, Stochastic Process, Queueing Theory, etc.
 Applied Mathematics
 Data Analysis and Data Mining
 Theory of Statistics (James E. Gentle)
 Think Stats, 2nd Edition: Exploratory Data Analysis in Python
 An Introduction to Statistical Learning: with Applications in R
 Learning Statistics with R (Daniel Navarro)
 The Elements of Statistical Learning: Data Mining, Inference, etc.
 Introduction to Statistical Thinking, with R, without Calculus