Handbook of univariate and multivariate data analysis with IBM SPSS / Robert Ho.
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TextPublication details: Boca Raton : CRC Press, c2014.Edition: 2nd edDescription: xxiii, 561 p. ; illISBN: - 9781439890219 (hardcover : alk. paper)
- 000SA.055 23 H678
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SA.055 H678 (Browse shelf(Opens below)) | Available | 136056 |
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| 000SA.055 F463 Basics of matrix algebra for statistics with R / | 000SA.055 G618 Survey of statistical network models / | 000SA.055 H465 Statistical analysis and data display : | 000SA.055 H678 Handbook of univariate and multivariate data analysis with IBM SPSS / | 000SA.055 K93 Statistical modeling and computation / | 000SA.055 K96 Applied predictive modeling / | 000SA.055 M311 SAS for data analysis : |
Includes bibliographical references and index.
1. Inferential statistics and test selection--
2. Introduction to SPSS--
3. Multiple response--
4. t Test for independent groups--
5. Paired-samples t test--
6. One-way analysis of variance, with post Hoc comparisons--
7. Factorial analysis of variance--
8. General linear model (GLM) multivariate analysis--
9. General linear model: repeated measures analysis--
10. Correlation--
11. Linear regression--
12. Factor analysis--
13. Reliability--
14. Multiple regression--
15. Multiple discriminant analysis--
16. Logistic regression--
17. Canonical correlation analysis--
18. Structural equation modeling--
19. Nonparametric tests--
Appendix--
Bibliography--
Index.
Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. This second edition now covers more topics and has been updated with the SPSS statistical package for Windows. New to the Second EditionThree new chapters on multiple discriminant analysis, logistic regression, and canonical correlatio.
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