The book presents an overview of multivariate statistics and their place in research. It describes the appropriate context for -- and the types of empirical questions that can best be addressed by -- each technique or family of techniques, as well as the distribution assumptions that must be met for the analysis to be meaningful. The most commonly used multivariate techniques are examined in detail: multiple regression and correlation, path analysis, principal-components analysis, exploratory and confirmatory factor analysis, multidimensional scaling, analysis of cross-classified data, logistic regression, multivariate an alysis of variance (MANOVA), discriminant analysis, and meta-analysis. Statistical notations are explained, underlying assumptions are described, and terms are defined clearly and understandably. Concepts and symbols are presented with minimal use of formulas and a generous use of real-world research examples. Each chapter also includes suggestions for additional reading and a glossary of statistical and related terms.
Reading and Understanding Multivariate Statistics
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74 of 75 people found the following review helpful:
4.0 out of 5 stars
Excellent Introductory Text for Non-Statisticians,
By
This review is from: Reading & Understanding Multivariate Statistics (Paperback)
As someone who has tried to teach multivariate statistics to non-statistician graduate students for the past 5 years, I have found this to be a very valuable and clearly-written text. As advertised and as the previous reviewer noted, the text is largely free of complex statistical equations and instead has clear descriptions of each type of test as well as common applications of that test. It is a perfect introduction for students who are intimidated by numbers and equations yet need to know about multivariate statistics for their graduate studies. The book has several weaknesses that I found require supplementing with other texts. For one, there is no tie-in with major computerized statistical applications like SPSS and SAS nor are there example exercises for students to run and interpret statistical tests for themselves. I have found such exercises to be invaluable in teaching the meaning and uses of multivariate tests. There also should have been a discussion of general issues that cut across the different multivariate tests such as data cleaning, data transformation, the role of correlation matrices and the like and so on. For coverage of these issues, I have found it helpful to use chapters from Tabachnik and Fidel's Using Multivariate Statistics text. Finally, a number of tests, such as survival analysis are not covered in this text, though a second volume by the same authors does cover survival analysis as well as other techniques and should be considered as a companion volume as well. In sum, this is an excellent and unusually clearly written text that is ideal for non-statistician graduate students in the social sciences. More in-depth analysis of important issues related to multivariate statistics and classroom exercises using statistical computer applications requires augmenting this text with additional readings.
76 of 79 people found the following review helpful:
5.0 out of 5 stars
Finally! A statistics book in English instead of statistese!,
By A Customer
This review is from: Reading & Understanding Multivariate Statistics (Paperback)
The book is an overview of a variety of multivariate statistical techniques. The book is geared as a companion to a heavy duty stats textbook, with the purpose of providing conceptual discussions of each of the techniques. And it succeeds brilliantly. The authors of each chapter treat the topic statistic with very little, if any Greek, plenty of concrete examples, and clearly delineate the assumptions of the statistical procedure, when it is appropriate and inappropriate to use the procedure, and how to interpret the results of the analysis. If what you want is simply to get a good, practical, conceptual understanding of a statistical procedure and its uses, without any of the theoretical, mathematical derivations, this is the book for you!! This book literally saved my grade in my multivariate stats class. No grad student should be without this.
42 of 44 people found the following review helpful:
5.0 out of 5 stars
I read it - and I understood it!,
By debvh (New Jersey) - See all my reviews
This review is from: Reading & Understanding Multivariate Statistics (Paperback)
"Reading and Understanding Multivariate Statistics" achieves exactly what its title implies. Geared toward non-statisticians in behavioral and social science fields, this book provides clear and reasonably simple explanations of some of the most common multivariate analyses. Each chapter focuses on a different analysis and presents its conceptual underpinnings, underlying assumptions, and basic procedures with a minimum of equations and many concrete examples. It does not teach you how to perform the analyses but does provide references for those who wish to get more detailed information. As a research scientist who doesn't always remember everything I learned in graduate statistics class, I find this book an invaluable aid keeping up with the current literature in my field and in making the most of statistical consultations. This book is ideal for anyone whose job requires them to be a "consumer" of research; for researchers who wish to further their understanding of data analysis; and as a companion text for graduate statistics classes.
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pupil light response, panic disorder study, conditional odds, experimentwise alpha, occasional marijuana use, derivation study, perceived relatedness, prior wealth, expected misclassification costs, logistic regression curve, induction score, nominal alpha level, factor loading coefficients, potential third variables, having used marijuana, oblique model, psychosomatic model, proximity data, local minimum solutions, multivariate effect, first discriminant function, predicting bankruptcy, prior criminal convictions, nonrecursive models, concurrent symptoms Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Psychological Bulletin, Beverly Hills, United States, Newbury Park, Human Relations, South Never, American Statistical Association, None Over, None Teenager, None Young, Academic Press, Los Angeles, San Diego, University of Michigan, Affect Intensity Measure, Burglary None, Child Development, Elsevier Science, National Adult Reading Test, Tests of Homogeneity Within Groups Defined, Unarmed None New!
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pupil light response, panic disorder study, conditional odds, experimentwise alpha, occasional marijuana use, derivation study, perceived relatedness, prior wealth, expected misclassification costs, logistic regression curve, induction score, nominal alpha level, factor loading coefficients, potential third variables, having used marijuana, oblique model, psychosomatic model, proximity data, local minimum solutions, multivariate effect, first discriminant function, predicting bankruptcy, prior criminal convictions, nonrecursive models, concurrent symptoms Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Psychological Bulletin, Beverly Hills, United States, Newbury Park, Human Relations, South Never, American Statistical Association, None Over, None Teenager, None Young, Academic Press, Los Angeles, San Diego, University of Michigan, Affect Intensity Measure, Burglary None, Child Development, Elsevier Science, National Adult Reading Test, Tests of Homogeneity Within Groups Defined, Unarmed None New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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11
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- Handbook Of Consumer Behavior, Tourism, And The Internet (Journal of Travel & Tourism Marketing Monographic Separates) by Juline E. Mills on page 75, page 76, and page 77
- Research Design in Social Research by David de Vaus in Back Matter
- Encyclopedia of Language and Education: Volume 4: Second Language Education (v. 4) by G. Richard Tucker on page 41
- Designing and Reporting Experiments in Psychology (Open Guides to Psychology) by Peter Harris in Back Matter
- Health Psychology: Theory, Research and Practice by David F. Marks in Front Matter
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