Syllabus Schedule Project A Project B Home


MGS 8040: Data Mining Fall 2017


Thursdays 5:30 9:45 PM

Buckhead Center

(200 Tower Place) Room 413

CRN: 82481





Assignments Due

(Post to iCollege)

Overview / Understanding Data / Preliminary Analysis

Week 1: 8/17


Introduction DM Overview

Regression Review

Simple Regression

Shoe size data


Data and Cows in India


Notes Simple Regression

Notes Multiple Regression


Solution to Exercise

Does p-value matter?


Interaction Effect

Week 2: 8/24

Understanding Credit Data

Equifax / Experian / Trans Union


The Initial Client Meeting


Introduction to SAS

SAS Training at UCLA

Notes Initial Client Meeting

Sample Design Exercise

Solution to Exercise

Data Cleaning

Notes Basic SAS Analysis
The Little SAS Book

By Delwiche & Slaughter

Data1 subset in Excel

1.   Regression Analysis

Regression Dataset


(due 8/24 by 11:59 PM. To iCollege)

Week 3: 8/31

5:30 to 6:30 PM: Guest Lecture

Jon Atteberry

Christina Chang

Statistical Modeling

Lexis Nexis


Data Cleaning

Dummy Variable Definition


Class Handout

Solution to Handout


Data Warehouse introduction

Books by Edward Tufte.

Gallery of Data Visualization

WHO visualization

SAS Programs for dummies, Regression and Scoring

2. Application Dep. Var, Outcome, Sample time frame


3. SAS assignment

Folder Instructions


(both due 8/31) by 11:59 PM. Post to iCollege as separate Assignments).

Week 4: 9/7

Test 1 (5:30 7:00 PM)


7:15 PM - Intro to Logistic Regression,

Discriminant Analysis

4. Crosstabs, Dummy decisions

(due Saturday 9/2) by 11:59 PM so you get feedback before the test)

Predictive Modeling/Validation/Segmentation/Association

Week 5: 9/14

Validation KS Test


7:15 - 9:45 PM: Guest Lecture:

Gregg Weldon, CAO,

Analytics IQ Inc.

Logistic Reg, Classification Trees.


Please print files below, bring to class (or bring laptops)

Logistic Regression

Logistic Reg SAS program

Classification Trees


Week 6: 9/21

Effectiveness of models A review of methods



Cluster Analysis

SPSS Output (Cluster)

Research Paper on Model Effectivenss

Factor Analysis

Clustering Paper

5. Discrim, KS

(due 9/21 by 11:59 PM)


SAS Programs for Regression/Scoring

Week 7: 9/28

Test 2 (5:30 7:00 PM)


Association Techniques, Monitoring Reports, Review


6. Clustering

(due Saturday, 9/23 by 11:59 PM - Do with your project team)

Week 8: 10/5

Project Presentations 5:30 to 7:30/7:45 PM



Project Reports Due [Guidelines]

Sample Final Project