Introduction to Statistical Thought

Introduction to Statistical Thought grew out of my teaching graduate and undergraduate statistics courses for many years, and from my experience as a statistical consultant and collaborator. I wanted to write a text that

explains how statisticians think about data,

introduces modern statistical computing, and

has lots of real examples.

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. "Statistical thinking" means 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. "Likelihood emphasis" means 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. R and accompanying manuals are available for free download from http://www.r-project.org.

Here is a copy of a book review from JASA, December, 2006.

Introduction to Statistical Thought is not finished, and probably never will be, but is sufficiently complete to be used as a course text by knowledgable instructors. Material will be added and corrections will be made. Let me know your suggestions and any errors you find. And please let me hear about your experience reading the book or using it as a text.

Introduction to Statistical Thought is available for free download. Because it is not handled by a commercial publisher, it will not be advertised as most commercial texts are. Therefore it must rely on word of mouth. If you like it, please let others know. If you don't like it, please let me know, especially if you can say why. I don't promise to adopt your suggestions but I do promise to take them seriously.



Downloads:

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USER CONTRIBUTIONS Are you able to contribute an example, an exercise, solutions, new data sets, new material, anything else? Email me, and I may be able to add it to this site, with proper attribution, of course.





A reader, luism dot guirola at gmail dot com writes, "... the book is very comprehensive and covers a considerable amount of material. ... Since there is a massive amount of statistics contained in it, going through the whole material may be an unattainable goal for those who, like me, are time-constrained or not interested in every single chapter. Some guidance in the form of a How to use this book section would probably improve the text to make easier to build selective courses from it. ... Another possible avenue for improvement would be a bibliographical essay at the end of the book. ... a pair of pages to situate the material of the book between where you should be coming from (what you are assumed to know and where to find guidance to catch up) and where to go from here (further reading) would help."





If any readers would like to write the guides that Luis suggests, or collaborate with him in writing them, I would be happy to add them to the book's website.









Introduction to Statistical Thought by Michael Lavine is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.