Download PDF Handbook of Applied Multivariate Statistics and Mathematical ModelingFrom Academic Press
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Handbook of Applied Multivariate Statistics and Mathematical ModelingFrom Academic Press
Download PDF Handbook of Applied Multivariate Statistics and Mathematical ModelingFrom Academic Press
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Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.
- Sales Rank: #3804997 in Books
- Published on: 2000-05-10
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x 1.56" w x 6.14" l, 2.56 pounds
- Binding: Hardcover
- 721 pages
From the Back Cover
The Handbook of Applied Multivariate Statistics and Mathematical Modeling enables researchers to understand which techniques are useful for answering different kinds of questions. Statistics are presented as an easy to use tool that does not require knowledge of the mathematical basis of the technique in order to be effective. Coverage includes 95% of techniques in common usage and each chapter discusses the data requirements for each technique, decisions necessary to perform the analysis, and interpretation of results. In depth examples provide applications of procedures to data in the biological and social sciences.
About the Author
Howard E.A. Tinsley, University of Florida, Gainesville.
Steven D. Brown, Loyola University Chicago, Wilmette, Illinois.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Extremely varied, rewarding survey of the field for the ...
By Roland B. Stark
Extremely varied, rewarding survey of the field for a student of statistics/data analysis/statistical modeling/data mining. Treat each technique in some depth. I appreciated the way the 25 or so contributors explained the conceptual basis for a given approach, its purpose, and some of its pitfalls in addition to showing how it might be applied.
If you're the type who pokes through the menus of statistical software programs, gets curious about methods listed there, and wishes you had introductions more helpful than those offered in the Help files, ... you may well drool over this collection. It actually straddles the world of the applied researcher and mathematical statistician. It features many "star" authors responsible for inventing or popularizing particular methods over the past 30 years.
Covers tools for assessing cross-sectional outcomes (linear, logistic, and multi-level regression); longitudinal change (survival analysis, covariance structure modeling); how variables or subjects might cluster together (factor analysis, cluster analysis, multidimensional and circular scaling); and on and on and on. Just don't expect complete step-by-step instruction.
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