IDS 472 Homepage

University of Illinois at Chicago
College of Business Administration
Department of Information & Decision Sciences

*IDS 472*	Statistics for Information Systems and Data Mining
*Semester*	Spring, 2002 (Term #012)

HOMEPAGE

*Time*	M W 2:00 - 3:15
*Place*	DH 118, except in L270 EPASW (CBA PC Lab) on Mondays, 14-Jan / 22-April
*Textbooks*	Required: Berry & Linoff, Data Mining Techniques (DMT) *Recommended: Berry & Linoff, Mastering Data Mining* (MDM)**

Staff

*Instructor*	Stanley L. Sclove, Professor, Information and Decision Sciences
Office	2418 UH
Telephone	Office (312) 996-2681 Dept (312) 996-2676
E-mail	slsclove@uic.edu
Web page URL	http://www.uic.edu/~slsclove
Office hours	14 Jan / 29-Apr, M 3:30-5:30 in CBA PC Lab, L270 EPASW (if not there, in Room 2418 UH)
TA	Senlin Wu, PhD Student in MIS
E-mail	swu6@uic.edu
Office hours	M W 12:15 - 1:45, in the CBA PC LAB (Room L270 EPASW)

Organization and Administration

Syllabus

Attendance

Course Calendar

Bibliography (FYI only: no readings assigned except the textbooks)

Errata to DMT

Suggestions for IDS Majors

Tasks in the course

Three homework assignments; two exams; and a final project.

Homework A	Nearest Neighbor Classification	Due M, 4-Feb-2002
Homework B	Classification	Due M, 11-Feb-2002
Exam #1	Review Qs for Exam #1 Solutions to same	W, 20-Feb-2002
Homework C	Classification Trees	Due W, 3-April-2002
Exam #2	Review Qs for Exam #2 Solutions to same	W, 17-April-2002
Project	Team Project for the Term	Due by 12:30 pm on W, 1-May-2002 Peer Evaluation Form

In regard to the exams, there may well be exam questions which are from lectures and not necessarily covered in the Review Qs. So, come to class, take notes, and study the notes between classes.

Labs
Lab #1a   Mon., 14-Jan.:   Distances
Lab #1b   Mon., 28-Jan.:   Nearest Neighbors
Lab #2    Mon., 4-Feb.:   Discriminant Analysis
Lab #3    Mon., 11-Feb.:   Discriminant Analysis - Quadratic
Lab #4    Mon., 18-Feb.:   Logistic Regression
Lab #5    Mon., 25-Feb.:   k-MEANS Clustering
Lab #6    Mon., 4-Mar.:   k-MEANS Clustering with Preprocessing
Lab #7    Mon., 11-Mar.:   Hierarchical Clustering
Lab #8    Mon., 25-Mar.:   Classification Trees
Lab #9    Mon., 1-Apr.:   Path Analysis
Lab #10   Mon., 8-Apr.:   Stratified Sampling Instructions    Spreadsheet
Lab #11   Mon., 15-Apr.:   Correspondence Analysis

DATA

Buy, Gender, Age, Income

Alpha radial tires data

Assets/Sales/Profits workbook

Credit Data

Iris Data

Heart Data

Correspondence Analysis of Smoking Data

Background Notes

Review of Business Statistics I-II Solutions

Notes on Vectors and Matrices

Notes on some Chapters and Other Topics

Memory-Based Reasoning: Chapter 9 Mon., 7-Jan./Wed., 23-Jan.; Notes on Ch. 9; Video: ABC "Nightline" show on MovieLens -- Helping You Find the Right Movies; Classification; Classification W, 30-Jan-02; Discriminant Analysis W, 6-Feb-02; Logistic Regression W, 13-Feb-02; Credit Scoring W, 13-Feb-02

Chapter 1 Why Data Mining?
An Introductory Note

Chapter 4 What Can Data Mining Do?
Notes for Ch. 4
Chapter 5 Data Mining Methodology: Outlier Detection: An Example

Chapter 7 Overview of Data Mining Techniques
Another type of technique: Path Analysis

Exam #1 Wed., 20-Feb-2002 Review Questions for Exam #1 Solutions to same
Exam 1 (posted 21-Feb) solutions to same (posted 21-Feb)

Chapter 10 Automatic Cluster Detection M, 25-Feb / W, 6-March

Notes on Ch. 10

Notes on "The Clustering of America"

to go with NOVA's "We Know Where You Live"

video on geodemographic databases and direct-mail marketing

Example: "You are What You Eat," by David J. Lipke, American Demographics, 10/1/2000. Marriott cooks up changes in campus dining with an inventive segmentation program

Video: Against All Odds: Inside Statistics Program 10: "Multidimensional Data"

Homepage for Sclove's cluster analysis package.

Chapter 12 Decision Trees W, 13-March / W, 27-March: Notes on Ch.12; Notes on CART; Tree for iris data; Classification regions from tree for iris data; Expected loss calculation from tree for iris data; Paper on employee retention

Chapter 13 Artifical Neural Networks W, 3-April / M, 8-April: Outline of lecture; Notes

Exam #2 Wed., 17-April-2002 Review Qs for Exam #2 Solutions to Rev Qs for Exam #2: posted 18-April:; Exam 2A solutions to same Exam 2B solutions to same

Chapter 14 Genetic Algorithms W, 10-April / W, 24-April

Reading: pp. 335-348; you may omit pp. 349-359.

Notes

Project Due by 12:30 p.m., Wed., 1-May-2002 Writing Tips

Links: Stock returns research links; Minitab Web Resources Site; Prof. Sclove's homepage

"What goes around, comes around." 1.6 billion movie tickets were sold in the U.S. and Canada in 1999. The last year that many tickets were sold was 1959. TIME, 29-Nov-1999.

latest update 18 April 2002