Class time for Spring 2002: Wednesday 6:30-9:20PM

Instructor: Dr. Chih-Yang Tsai,         Office: VLC 209A, TEL: 257-2934,

Email: tsaic@newpaltz.edu    URL: http://www.newpaltz.edu/~tsaic

BlackBoard Server : http://blackboard.newpaltz.edu

URL of this course outline: http://www.newpaltz.edu/~tsaic/courses/20525_1.html

Office Hours For Spring 2002:  W, F: 9:45-11:00AM,        W:  5:25-6:25PM       T: 2:00-2:30PM (before Spring break) and  S: 8:30-9:00AM(after Spring break)

Objective: This course covers a number of quantitative methods used to solve business problems in various functional areas. The focus is on problem formulation and interpretation of computer outputs obtained from solving the problem with software packages such as SPSS and EXCEL. Techniques covered in the course include multivariate statistical methods and linear programming. In addition, concepts of artificial neural networks and data mining are introduced. Projects designed to enhance students' analytical skills and computer proficiency are assigned to give students hands-on experience on applying quantitative models to solve problems arising from Finance, Marketing, Management, and Operations.  One emphasis in the course is on retrieving and organizing datasets obtained from a commercial database package for further analyses.

Textbook: Applied Multivariate Techniques, by Subhash Sharma, 1996, John Wiley & Sons

Software Packages: MS Excel, SPSS, DB2

All computer labs on campus are equipped with both Excel and SPSS.  If you would like to install them on your home computer, Excel can be purchased from campus bookstore and many retailers.  Prentice Hall publishes a student version of SPSS, [SPSS 10.0 for Windows Student Version, 1/e (ISBN 0-13-028040-2)].  You can order it online directly from Prentice Hall or other  retailers.  College Computer Center also provides accesses to SPSS and other software packages on its servers.  You need to download and install a package (citrix) on your PC.  It allows you to run your program remotely on the server.  However, the speed might be compromised.  Some course materials might be in postscript (with a file extension, ps) format.  To view and print a ps file on PC, you needs to download and install GSVIEW.  To view and print a PDF file, you need to download and install the software Acrobat Reader.  Access to IBM DB2 is done through the internet (telnet, SSH).

Access to Blackboard Server: All announcements, homework assignments, transparencies used in class lecture etc. will be made available on the blackboard server.  Every student will get an account for the course.  Please check the announcement periodically for new events (Events will also be announced in class.)

Grading Policy: There are two examinations.  No makeup exams are allowed unless there is a legitimate reason with supporting documents.

1. Examination I (30%):
2. Examination II (30%)
3. Projects (25%): There will be team projects as well as individual projects.  The project requires students to analyze problems, recommend a solution, compose a written report, and conduct an oral presentation.
4. Homework (15%): Assignments are due in a week.  No late homework will be accepted.

Syllabus:

1.	Review of Statistics and Linear Algebra: Chapters 1, 2, 3, and handouts
2.	Principal Components Analysis: Chapter 4
3.	Factor Analysis: Chapters 5, 6.
4.	Cluster analysis: Chapter 7
5.	Discriminant Analysis: Chapters 8, 9
6.	Linear Programming: Handouts
7.	Neural Network and Data Mining: Handouts
8.	Discussion of Students' Projects.

Research Resources:

Web sites for data sets:

    http://www.ics.uci.edu/~mlearn

    http://www.kdnuggets.com