大小：761页
格式：pdf

Joseph Hair, William Black, Barry Babin, Rolph Anderson
Description
For graduate and upper-level undergraduate marketing research courses.

For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.

Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques.

In this seventh revision, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.


Contents
I  Introduction
1  Introduction

II  Preparing For a MV Analysis
2  Examining Your Data
3  Factor Analysis

III  Dependence Techniques
4  Multiple Regression Analysis
5  Multiple Discriminate Analysis and Logistic Regression
6  Multivariate Analysis of Variance
7  Conjoint Analysis

IV  Interdependence Techniques
8  Cluster Analysis
9  Multidimensional Scaling and Correspondence Analysis

V  Moving Beyond the Basic Techniques
10  Structural Equation Modeling: Overview
10a  Appendix – SEM
11  CFA: Confirmatory Factor Analysis
11a  Appendix – CFA
12  SEM: Testing A Structural Model
12a  Appendix – SEM

APPENDIX
A  Basic Stats