Multivariate Data Analysis Chapter 12 - Emerging Techniques

1. Multivariate Data AnalysisChapter 12 - Emerging Techniques MIS 6093 Statistical Method Instructor: Dr. Ahmad Syamil

2. Chapter 12Introduction • The Information Avalanche • Analysis Without Statistical Inference • Topics Covered in this Chapter • Data Warehousing and Data Mining • Neural Networks • Resampling

3. Chapter 12Data Warehousing and Data Mining • What are data warehousing and data mining? • Fundamental Concepts in Data Warehousing • Operating a Data Warehouse • Data Definitions • Operational versus Analytical Data • Primitive versus Aggregated Data • Metadata • Summary

4. Chapter 12Data Warehousing and Data Mining Cont. • Fundamental Issues in Data Mining • What’s Different Versus What’s the Same In Data Mining? • Some Differences • Some Similarities • Exploration Versus Confirmation • Data Mining Techniques • Query • Visualization • Multivariate Statistical Tools • Association Rules • Decision Trees • Neural Networks • Genetic Algorithms • A Multivariate Researcher’s Perspective • Summary

5. Chapter 12Neural Networks • Basic Concepts of Neural Networks • Types of Neural Network Models • Nodes • Neural Network • Learning

6. Chapter 12Neural Networks Cont. • Estimating A Neural Network Model • Data Preparation • Sample Size • Examining the Data • Defining the Model Structure • Model Estimation • Evaluating model results • Model Validation • Summary • Using A Neural Network For Classification • Summary

7. Chapter 12Resampling • A Brief Review of Parametric Inference • Basic Concepts in Resampling • Resampling Methods • Jackknife versus Bootstrap • Limitations • An Example of Resampling and Multiple Regression • Summary

8. Chapter 12 • Summary • Overview • Questions • References ……end