Multivariate data analysis / by Joseph F. Hair and et al.
Material type:
TextSeries: ; Multivariate data analysisPublication details: New Delhi : Pearson Education(Singapore) , 2023Edition: 8th edDescription: xvii, 800p.: ill.; 25 cmISBN: - 9789353501358
- 519.535 HAM
Books
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Statistics Discipline
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New Arrival Book 2023
| Item type | Current library | Collection | Shelving location | Call number | Copy number | Status | Date due | Barcode | |
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Books
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KU Central Library | Rack No. : 16 Annex : 01 Shelve No. : A-03 | Reference Section (Non-Issuable Books) | 519.535 HAM 2023 (Browse shelf(Opens below)) | C-1 (NI) | Not For Loan | 52261 | ||
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Books
|
KU Central Library | Rack No. : 16 Annex : 01 Shelve No. : A-03 | Reference Section (Non-Issuable Books) | 519.535 HAM 2023 (Browse shelf(Opens below)) | C-2 (NI) | Not For Loan | 52262 |
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| 519.5 WOI 2023 Introductory Econometrics : A Modern Approach / | 519.53 AGB Basic statistics / | 519.535 HAM 2023 Multivariate data analysis / | 519.535 HAM 2023 Multivariate data analysis / | 519.536 DRA 1998 Applied regression analysis / | 519.536 DRA 1998 Applied regression analysis / | 519.536 MOD 2016 Design and analysis of experiments / |
includes index
Chapter 1 Overview of Multivariate Methods
Section 1: Preparing for Multivariate Analysis
Chapter 2: Examining Your Data
Section 2: Interdependence Techniques
Chapter 3: Exploratory Factor Analysis
Chapter 4: Cluster Analysis
Section 3: Dependence Techniques
Chapter 5: Multiple Regression
Chapter 6: MANOVA: Extending ANOVA
Chapter 7: Discriminant Analysis
Chapter 8: Logistic Regression: Regression with a Binary Dependent Variable
Section 4: Moving Beyond the Basic Techniques
Chapter 9: Structural Equation Modeling: An Introduction
Chapter 10: Confirmatory Factor Analysis
Chapter 11: Testing Structural Equation Models
Chapter 12: Advanced Topics in SEM
Chapter 13: Partial Least Squares Modeling (PLS-SEM)
Multivariate Data Analysis is an applications-oriented introduction to multivariate analysis for the non-statistician. The eighth edition incorporates pivotal advances in technology that will assist students in gaining a firm understanding of statistical and managerial principles so as to develop a "comfort zone" not only for the statistical, but also the practical issues involved
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