A Primer on Linear Models

This book PDF is perfect for those who love Mathematics genre, written by John F. Monahan and published by CRC Press which was released on 31 March 2008 with total hardcover pages 304. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related A Primer on Linear Models books below.

A Primer on Linear Models

Author	: John F. Monahan
File Size	: 40,6 Mb
Publisher	: CRC Press
Language	: English
Release Date	: 31 March 2008
ISBN	: 9781420062045
Pages	: 304 pages

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A Primer on Linear Models by John F. Monahan Book PDF Summary

A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods.

A Primer on Linear Models by John F. Monahan

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Multiple Regression by Paul D. Allison

"Presenting topics in the form of questions and answers, this popular supplemental text offers a brief introduction on multiple regression on a conceptual level. Author Paul D. Allison answers the most essential questions (such as how to read and interpret multiple regression tables and how to critique multiple regression results)

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Regression ANOVA and the General Linear Model by Peter Vik

Peter Vik's Regression, ANOVA, and the General Linear Model: A Statistics Primer demonstrates basic statistical concepts from two different perspectives, giving the reader a conceptual understanding of how to interpret statistics and their use. The two perspectives are (1) a traditional focus on the t-test, correlation, and ANOVA, and (2) a model-comparison

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Linear Models in Statistics by Alvin C. Rencher,G. Bruce Schaalje

The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains

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A First Course in Linear Model Theory by Nalini Ravishanker,Dipak K. Dey

This innovative, intermediate-level statistics text fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the author's introduces students to the mathematical and statistical concepts and tools that form a foundation for studying

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Applied Regression Analysis and Generalized Linear Models by John Fox

Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes

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Applied Linear Models with SAS by Daniel Zelterman

This textbook for a second course in basic statistics for undergraduates or first-year graduate students introduces linear regression models and describes other linear models including Poisson regression, logistic regression, proportional hazards regression, and nonparametric regression. Numerous examples drawn from the news and current events with an emphasis on health issues

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Linear Models and the Relevant Distributions and Matrix Algebra by David A. Harville

• Exercises and solutions are included throughout, from both the first and second volume • Includes coverage of additional topics not covered in the first volume • Highly valuable as a reference book for graduate students or researchers

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