Statistical Methods: A Geometric Primer by David J Saville (PDF)

Description

Are you an applied researcher or a statistics student? If so, have you ever wondered if there is any rhyme or reason behind the apparent jumble of ad hoc statistical “recipes” that are most commonly used by researchers? If you have, then this book is for you! Within its pages, the rhyme and reason are explained in a surprisingly simple, visual and appealing manner. The statistical methods referred to are those based on the “Normal” distribution. They include the paired and independent samples t tests, analysis of variance, and regression. The rhyme is explained by analysing four case studies, one for each of these topics. The key to the rhyme is to use elementary vector geometry. Then the crucial ideas are easily explained by drawing right-angled triangles and applying Pythagoras’ Theorem. “Keep it simple” has been our aim. The geometric ideas are first introduced and applied to data sets in two and three dimensions, before we gently introduce higher dimensional examples. Throughout, we use real data sets taken from real research studies, and take care to explain the interpretation of the statistical analyses. In this way, the book integrates the algebraic, numeric, geometric and practical aspects of these basic statistical methods. We hope that many students as well as practicing researchers and statisticians will enjoy this novel visual approach to these ideas.

User’s Reviews

Editorial Reviews: About the Author Dave Saville is a consulting statistician working in agricultural research; Graham Wood is a university professor involved in teaching statistical methods. They met and became friends when studying mathematics at the University of Otago, in Dunedin, New Zealand. Both have since worked for over forty years in their current fields.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐The book is indeed quite conservative in the quantity of material it seeks to impart. However, the result is the bare-bones essentials to a geometric interpretation of ANOVA, regression, and the t statistic. I plan to broaden my statistical understanding by consulting the more advanced books by the same authors. I found the systematicity of the presentation in this book to be easy for me to understand, and I hope that it carries into the further books.

⭐Could have been better. The underlying statistical method isn’t described well.

⭐This book was recommended to be by a colleague, and I am glad I purchased it. What a wonderful connection between Statistics, Geometry, and Vectors. The book is well organized, with theory derived through concrete examples. An easy read!

⭐Remarkably clear and accessible. The exercises are well designed to reinforce the key ideas in the presentation and the solutions explained thoroughly.

⭐Excellent book for understanding the geometry behind statistics. Clear writing style and good illustrations.

⭐This work has always put the concept of Statistical Methods in to a form that makes sense. It is brilliant and I highly recommend it.

⭐A different view and derivation

⭐Amazingly good…

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