Practical multivariate analysis / Abdelmonem Afifi, Susanne May, Virginia A. Clark.
Material type:
TextSeries: Chapman & Hall/CRC texts in statistical science series ; 93Publication details: Parkway, NW : CRC Press, c2012.Edition: 5th edDescription: xix, 517 p. : ill. ; 24 cmISBN: - 9781439816806
- QA 278 .Af42 2012
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|
Graduate Studies
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Aklatang Emilio Aguinaldo-Information Resource Center Graduate Studies | Graduate Studies | QA 278 .Af42 2012 (Browse shelf(Opens below)) | In transit from Aklatang Emilio Aguinaldo-Information Resource Center to DLSU-D GRADUATE STUDIES since 04/14/2023 | 3AEA2012001246 |
Rev. ed. of: Computer-aided multivariate analysis. 4th ed. c2004.
"A Chapman & Hall book."
Includes bibliographical references and index.
This new version of the bestselling Computer-Aided Multivariate Analysis has been appropriately renamed to better characterize the nature of the book. Taking into account novel multivariate analyses as well as new options for many standard methods, Practical Multivariate Analysis, Fifth Edition shows readers how to perform multivariate statistical analyses and understand the results. For each of the techniques presented in this edition, the authors use the most recent software versions available and discuss the most modern ways of performing the analysis. New to the Fifth Edition Chapter on regression of correlated outcomes resulting from clustered or longitudinal samples Reorganization of the chapter on data analysis preparation to reflect current software packages Use of R statistical software Updated and reorganized references and summary tables Additional end-of-chapter problems and data sets The first part of the book provides examples of studies requiring multivariate analysis techniques; discusses characterizing data for analysis, computer programs, data entry, data management, data clean-up, missing values, and transformations; and presents a rough guide to assist in choosing the appropriate multivariate analysis. The second part examines outliers and diagnostics in simple linear regression and looks at how multiple linear regression is employed in practice and as a foundation for understanding a variety of concepts. The final part deals with the core of multivariate analysis, covering canonical correlation, discriminant, logistic regression, survival, principal components, factor, cluster, and log-linear analyses. While the text focuses on the use of R, S-PLUS, SAS, SPSS, Stata, and STATISTICA, other software packages can also be used since the output of most standard statistical programs is explained. www.alibris.com/lac.
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