Regression, ANOVA, and the General Linear Model
A Statistics Primer
- Peter Vik - Pacific University, Forest Grove, OR, USA
Easy to read even for the undegraduates with limited knowledge of statistics as provides a step-by-step approach to understanding ANOVA and regression techniques.
An extremely good book that breaks down the subject in to understandable pieces
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.
An indispensable reference that redefines the position of the linear model and clarifies statistical approaches in research. The text is engaging and provides relevance as both an introductory tome and dip-in reference.
Clealry laid out text with good examples. Stress free reading !
Excellent book for anybody performing research in sports science.
This is an excellent and unique statistics text that bridges the gap between linear modelling approaches and the traditional test-focussed perspective. Worthy of comparison with Rich Zeller and Ed Carmines classic text, explaining the essential underpinning concepts rather than trying to teach statistical tests by rote.
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.
