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Multivariate data analysis / by Joseph F. Hair and et al.

By: Contributor(s): Material type: TextTextSeries: ; Multivariate data analysisPublication details: New Delhi : Pearson Education(Singapore) , 2023Edition: 8th edDescription: xvii, 800p.: ill.; 25 cmISBN:
  • 9789353501358
Subject(s): DDC classification:
  • 519.535  HAM
Contents:
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)
Summary: 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
Item type: Books List(s) this item appears in: Statistics Discipline | New Arrival Book 2023
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Holdings
Item type Current library Collection Shelving location Call number Copy number Status Date due Barcode
Books 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-1 (NI) Not For Loan 52261
Books 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

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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