Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition

Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition

764e6 Marketplace Analysis 41PX30TJ2CL. SL160  Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition

This classic multivariate statistics book has become the introduction of choice for researchers and students with a minimal mathematics background. In addition to providing a review of fundamental statistical methods, it provides a basic treatment of advanced computer-based multivariate analytical techniques; including correlation and regression analysis, analysis of variance, discriminant analysis, factor analysis, cluster analysis, and multidimensional scaling. The conceptual treatment emphasizes the rationales, applications, and interpretations, rather than the theoretical mathematical aspects of the most commonly used data analysis techniques in use today, closing the gap between spiraling technology and its intelligent application, providing students and researchers with a decided advantage in their future studies and careers.

Its conceptual non-mathematical approach is especially helpful to students, researchers, and managers in the social and health sciences, education, and business. It is also the ideal springboard for those who will pursue advanced study of these powerful multivariate techniques.

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  1. John C. Dunbar says:
    19 of 19 people found the following review helpful
    5.0 out of 5 stars
    Great at giving rationale behind the methods, May 29, 2001
    By 
    John C. Dunbar (Sugar Land, TX United States) –
    (REAL NAME)
      

    This review is from: Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition (Paperback)

    This book is unlike most other statistics books in that it spends lots of time giving you the rationale behind the methods.

    I found this to be very helpful. This was the book that helped fill in the blanks on other (college-style) texts. This is not an easy book to read. It is a clear and quick explanation of the logic behind multivariate statistics. Sometimes that logic is involved, but you can master it by reading more slowly.

    I think after finishing this book, or in parallel with it, you would want another text that has lots of practical exercises.

    Highly recommended… if you’re one of those that wants to know the “why” behind the “what”.

    John D.

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  2. David Bell says:
    16 of 16 people found the following review helpful
    5.0 out of 5 stars
    Multivariate Statistical Analysus, December 13, 1999
    By 
    David Bell (England) –

    This review is from: Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition (Paperback)

    Having spent the last couple of months trying in vain to find a book on Multivariate Analysis which doesn’t assume a degree in mathematics. This book is absolutely wonderful! No assumptions are made, other than simple mathematical knowledge, thus making it a must for those researchers and scientists simply looking for some techniques for visualising high-dimensional data. A thoroughly worthwhile book and cheap at half the price!

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  3. Anonymous says:
    15 of 15 people found the following review helpful
    5.0 out of 5 stars
    An intuitive introduction–not strictly mathematical., June 8, 1996
    By A Customer
    This review is from: Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition (Paperback)

    Kachigan has successfully reduced his introduction to multivariate statistics to descriptive, if somewhat figurative, explanations of the ideas behind the subject, without constantly resorting to a formulas-only approach.Some authors make the mistake of forgetting what that key word in their title means–introduction: an explanation in terms understood by those unfamiliar with the subject.But Kachigan uses analogies and examples to explain the concepts of multivariate statistical analysis to the benefit of those who want to understand the concept before they attempt the practice. This is always the best way to learn ideas. Books that ignore the need to have a clear idea of why things are done do a disservice to those who study them. After reading Kachigan’s direct and concise explanations, I wished that I had found him sooner. I intend to purchase his “Statistical Analysis: An Interdisciplinary Introduction to Univariate and Multivariate Methods” as a reference to occasionally check my own explanations of statistical methods in my research papers. My professors say that my understanding of these concepts seems to have improved. They should not be surprised–they recommended this book.

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