Regression, ANOVA, and the General Linear Model
A Statistics Primer
- Peter Vik - Pacific University, Forest Grove, OR, USA
Supplements
A selection of diverse conceptual and computational practice problems is provided for each chapter of the book, minus the introduction. Students are encouraged to use them as a study aid and instructors are encouraged to use them as a homework and/or testing tool.
“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.”
“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.”
“The text includes simple descriptions of complex mathematical concepts that are the foundation of statistics in the social sciences.”
“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.”
“…the author really takes the readers step by step and makes the material easy to follow even for readers without extensive mathematics backgrounds.”
The book stands out with its clarity and structure which allows students to easily orientate themselves in elementary methods of empirical research. The genral approach enables student's to derive further methods and adopt knowledge to various kinds of statistical software.
A very useful book which focuses on some of the more commonly used tests for biological sciences
Vik covers clearly and simply the mathematical concepts underlying vast tools in statistical methods. The examples are very helpful and are well explained in that a student with no statistical background can grasp the concepts therein without much difficulty. I would recommend students to supplement this text with their primary text when they take courses in statistics.
Although I really like this book (and recommend it as a supplemental text for my students), I did not adopt it. The book has very little support material (e.g., PowerPoint slide, images, homework and test problems, sample data sets), which makes it very difficult for me to choose it over other texts that have this material -- note: this is especially true for the data sets, which are difficult to create. Also, book does not have much coverage for follow-up analyses for interactions in multiple regression or factorial ANOVA. Although this is a complex topics and somewhat beyond the scope of the book, it is one that I have to cover in my class.
Clealry laid out text with good examples. Stress free reading !
Sage College Publishing
