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Rating:  Summary: Excellent book Review: If you are in a situation like me, then this might be the best book. I read some introductory long ago at university. A few years from now I needed to refresh on the subject and get a little deeper. I have browsed or read some other books, but this is now my number one choice for reference. It starts very gently with e.g. spelled out examples on matrix addition. It ends with (by my standards) advanced topics like eigenstructures, quadratic forms, generalized inverses etc. I admire the writing style which is compact, precise and at the same time a little relaxed.
Rating:  Summary: A great introduction to mathematics of statistical analysis Review: There are a lot of people out there who do statistical analysis but who do not possess the mathematical knowledge underpinning a lot of what they are doing (i.e., linear algebra and some calculus). Most of the time people can get away with using stastical software as a sort of 'black box' and not worry about the math. But there are situations when having the background knowledge is crucial.This book does an excellent job of facilitating self-study of the math underpinning multivariate statistical analysis ... namely, linear (matrix) algebra and some calculus. Each chapter has a set of questions and ALL of the answers are provided in the book (handy for self-study). The one slight critique of this book I can give is that I wish the book did more on the calculus aspects. However, that is a minor comment and the knowledge that this book imparts of linear algebra to self-learners is extremely valuable.
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