Regression, ANOVA, and the General Linear Model : A Statistics Primer - Peter Wright Vik

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Regression, ANOVA, and the General Linear Model

A Statistics Primer

By: Peter Wright Vik

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Paperback | 14 January 2013

At a Glance

Paperback
344 Pages

Dimensions(cm)
23.5 x 19.05 x 1.83

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$298.10

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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 approach using General Linear Models (GLM). This book juxtaposes the two approaches by presenting a traditional approach in one chapter, followed by the same analysis demonstrated using GLM. By so doing, students will acquire a theoretical and conceptual appreciation for data analysis as well as an applied practical understanding as to how these two approaches are alike.

Industry Reviews

"I believe that when students are taught about statistics using the approach of this text, they have a MUCH deeper understanding and appreciation of the material. It is really fantastic." -- Jeffrey A. Ciesla "The author does a really nice job of explaining the General Linear Model (GLM) by comparing it to hypothesis testing and showing [some of] its real-world applicability." -- Alfred F. Mancuso "The text includes simple descriptions of complex mathematical concepts that are the foundation of statistics in the social sciences." -- Lela Rankin Williams "I think the book provides a nice step-by-step approach to understanding ANOVA and regression techniques. The author does an excellent job breaking down the different components of these statistical techniques while capturing the attention of the reader." -- Manfred van Dulmen "...the author really takes the readers step by step and makes the material easy to follow even for readers without extensive mathematics backgrounds." -- Kamala London

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