Reading and Understanding Multivariate Statistics

I haven’t gotten that far, but I think I’m starting to understand the writing style employed.It’s a good book but one probably needs to have a background in Single Variable Statistics to understand a lot of concepts discussed. What’s more, it can be quite theoretical instead of just relying on examples to make a point.

Lawrence Grimm and Paul Yarnold have written this book for researchers who need a better understanding of a variety of multivariate statistical methods to read and evaluate published research. They note that this need is not well-addressed by most multivariate statistics textbooks, which "...are not written for the consumer of research or the novice to a particular statistical method. They are much more focused on the fine details of algorithms and formulas for analyzing data."This book has a more applied focus. It describes the fundamental concepts of each multivariate procedure, reviews the statistical assumptions and terminology associated with it, and demonstrates how each procedure can be used to analyze data from real research studies. Although the authors assume no prior learning about multivariate statistics, they do assume their readers are familiar with basic univariate methods. Following an introductory chapter on statistical foundations, the book contains chapter-length discussions of nine multivariate methods used in psychology, business, and related fields. The methods are: multiple regression, path analysis, factor analysis, multidimensional scaling, cross-classified data analysis, logistic regression, multivariate analysis of variance, discriminant analysis, and meta-analysis.The authors present concepts clearly and illustrate their use with extended examples. The book is recommended as a supplemental resource to the primary text in a multivariate analysis class. It is also recommended as a reference for practicing researchers as they review literature and consider adopting new methods. Readers may also benefit from the authors' subsequent book,  Reading and Understanding More Multivariate Statistics: , which focuses on scales of measurement.

This is a good book, a concise and accurate reflection on some uses of concepts in multivariate. These are quite clearly and well written. I recommend the book to everyone. Unfortunately, the book touches on only a few of the concepts and leaves, for example, mixed methods, which is the most frequently used multivariate method today. Still I highly recommend this book to learners as it will enrich their understanding.

This book made the statistics super easy for me to understand. I highly recommend it to younger students and occasionally re-read for a brush-up on the statistics it covers.

Good

I've long wanted a better explanation of Eigenvectors and Eigenvalues than I recieved in a econometrics or statistics textbook. This book gives me an incredibly clear understanding of what they are. Now when I look back at the mathematical interpretation again it means so much more. This is a fantastic book that would highly recommend to anyone wanting a clear conceptual understanding of these sophisticated topics. 5 stars, no questions about it!

This book is an excellent high-level overview of multivariate statistics and the techniques for working with multivariate data.It doesn't go into detail making it a very good read for people wanting to learn multivariate concepts.

I needed this book for some advanced Stats explainations - it's excellent for this - you need to have already taken and understood basic Statistics first before using this book for explainations - otherwise you'll have to go back and relearn basic Stats.

Reading and Understanding MORE Multivariate Statistics this is a very unusual book it expleian how the calculation are carried and what they mean, a very interesting book, its companion books is equally good.

Very good book! Advised if you want to really understand the tests you are using