Page 286 - DMGT404 RESEARCH_METHODOLOGY

Research Methodology Hitesh Jhanji, Lovely Professional University

Notes Unit 13: Multivariate Analysis

CONTENTS
Objectives
Introduction
13.1 Multivariate Analysis
13.1.1 Multiple Regression

13.2 Discriminant Analysis
13.3 Conjoint Analysis
13.4 Factor Analysis
13.4.1 Principle Component Factor Analysis

13.4.2 Rotation in Factor Analysis
13.5 Cluster Analysis
13.6 Multidimensional Scaling (MDS)
13.7 Summary
13.8 Keywords
13.9 Review Questions

13.10 Further Readings

Objectives

After studying this unit, you will be able to:
 Explain the concept of multivariate analysis

 Classify the multivariate analysis
 Define the Discriminant Analysis and Conjoint Analysis
 Discuss the Factor Analysis and Cluster Analysis

 State the Multidimensional Scaling (MDS)

Introduction

As the name indicates, multivariate analysis comprises a set of techniques dedicated to the
analysis of data sets with more than one variable. Several of these techniques were developed
recently in part because they require the computational capabilities of modern computers.
Multivariate analysis (MVA) is based on the statistical principle of multivariate statistics, which
involves observation and analysis of more than one statistical variable at a time. In design and
analysis, the technique is used to perform trade studies across multiple dimensions while taking
into account the effects of all variables on the responses of interest. Sometimes, the marketers
will come across situations, which are complex involving two or more variables. Hence, bivariate
analysis deals with this type of situation. Chi-Square is an example of bivariate analysis.

280 LOVELY PROFESSIONAL UNIVERSITY