Multivariate Data Analysis Chapter 1 - Introduction

1. Multivariate Data AnalysisChapter 1 - Introduction MIS 6093 Statistical Method Instructor: Dr. Ahmad Syamil

2. Chapter 1 • What is Multivariate Analysis? • Impact of the Computer Revolution • Multivariate Analysis Defined

3. Chapter 1 • Some Basic Concepts of Multivariate Analysis • The Variate • Measurement Scale • Nonmetric Measurement Scales • Metric Measurement Scales • Measurement Error and Multivariate Measurement • Statistical Significance Versus Statistical Power

4. Chapter 1Types of Multivariate Techniques • Principal Components and Common Factor Analysis • Multiple Regression • Multiple Discriminant Analysis • Multivariate Analysis of Variance • Conjoint Analysis • Canonical Correlation

5. Chapter 1Types of Multivariate Techniques • Cluster Analysis • Multidimensional Scaling • Correspondence Analysis • Linear Probability Models • Structural Equation Modeling • Other Emerging Multivariate Techniques

6. Chapter 1 • A classification of Multivariate Techniques • Guidelines for Multivariate Analysis and Interpretation • Establish Practical Significance as well as Statistical Significance • Sample Size Affects All Results • Know Your Data

7. Chapter 1 • Guidelines for Multivariate Analysis and Interpretation (Cont.) • Strive for Model Parsimony • Look at Your Errors • Validate Your Results

8. Chapter 1 • A structured Approach to Multivariate Model Building • Stage 1: Define the Research Problem, Objectives, and Multivariate Techniques to Be Used • Stage 2: Develop the Analysis Plan • Stage 3: Evaluate the Assumptions Underlying the Multivariate Technique

9. Chapter 1 • Stage 4: Estimate the Multivariate Model and Assess Overall Model Fit • Stage 5: Interpret the Variate(s) • Stage 6: Validate the Multivariate Model

10. Chapter 1 • Databases • Primary Database • Perceptions of HATCO • Purchase Outcomes • Purchaser Characteristics • Other Databases

11. Chapter 1 end…