Objectives Understand and define various approaches used for data mining, cluster analysis, discriminant analysis, and the associated rule of mining. Be familiar how to use XLMiner for classification logistic regression an

Overview

1. Cluster analysis
2. Classification techniques
3. Association rule mining
4. Cause and effect modeling

Objectives

• Understand and define various approaches used for data mining, cluster analysis, discriminant analysis, and the associated rule of mining.
• Be familiar how to use XLMiner for classification logistic regression and how to develop association rules.

• Chapter 10

students will answer some or all of the following:

• Explore, define and apply each week’s tools to recommended data.
• Analyze, summarize and visualize the problem to generate plausible solutions.
• Provide recommendations regarding the specific data.
• In addition to the case study, the data can be downloaded from the text website.

The case data are used to illustrate practical applications of the concepts discussed in this week’s lesson.