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A Primer on Linear Models (Chapman & Hall/CRC Texts in Statistical Science), by John F. Monahan
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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.
With coverage steadily progressing in complexity, the text first provides examples of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then introduces the basic algebra and geometry of the linear least squares problem, before delving into estimability and the Gauss–Markov model. After presenting the statistical tools of hypothesis tests and confidence intervals, the author analyzes mixed models, such as two-way mixed ANOVA, and the multivariate linear model. The appendices review linear algebra fundamentals and results as well as Lagrange multipliers.
This book enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models.
- Sales Rank: #827980 in Books
- Brand: Brand: Chapman and Hall/CRC
- Published on: 2008-03-31
- Released on: 2008-04-21
- Original language: English
- Number of items: 1
- Dimensions: 9.13" h x .69" w x 6.13" l, .95 pounds
- Binding: Paperback
- 304 pages
- Used Book in Good Condition
Most helpful customer reviews
2 of 4 people found the following review helpful.
Very good book!
By Thanh Hoang
I have been using this book for my class - Linear Statistical Models. This book is very easy to follow and has a lot of good exercises. Highly recommended!!!
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