Syllabus (Subject to further update)

BA 7000-081, Advanced Problem Solving with SAS, Spring 2009

Instructor: Zhangxi Lin

Office hours: 9:00-11:00a M-Th or by appointment, BA 708

Class Meeting: 11:00-12:00p Friday, BA363

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Course Description:

This course is designed for those who intend to further improve their problem solving skills using SAS programming as they already took SAS data mining class. The course is to cover three topics:

1. Decision trees and algorithm implementation

2. Implementing market intelligence by clustering modeling

3. Business optimization

Prerequisite: ISQS 6347, Preliminary SAS Programming

Learning Outcomes:

A student who successfully completes this course should be able to:

1. Master advanced data processing skills using SAS, specifically data preparation for analytics

2. Solve practically challenging problems with SAS programming, such as complex system simulation, data mining programming, operation research problems, etc.

3. Design and implement comprehensive algorithms

Assessment of Learning Outcomes:

Learning will be assessed by:

1. Four SAS problem solving projects

2. Homework assignments

3. A well-developed course notes representing students’ knowledge structure

4. Project Presentations

Required textbooks:

Data Preparation for Data Mining Using SAS® Software

SAS® Programming II

SAS® Programming III

Design and Analysis of Probability Surveys, SAS® Course Notes

SAS® Neural Network Modeling

SAS 9.1 Macro Language Reference (download)

Grading Policy:

Four term projects (400 points)
Homework (100 points)
Class participation (100 points)

The total is 600 points.

Projects:

There will be four projects:

1) Data preparation for data mining (Week 1-4)

2) System simulation (Week 5-8)

3) Data mining programming (Week 9-13)

4) Optimization (Week 14-16)

Note: Presentations are held in after each project.

University Policies

Requirements: Please contact me if you have any special requirements, or if I need to make special accommodations for you during the semester. I encourage you to visit with me about your progress in the course at any time.

Integrity. Academic dishonesty will not be tolerated. All students are required to adhere to the Texas Tech University Policy on Academic Honesty.

Civility in the Classroom. “Students are expected to assist in maintaining a classroom environment which is conducive to learning. In order to assure that all students have an opportunity to gain from time spent in class, unless otherwise approved by the instructor, students are prohibited from using cellular phones or beepers, eating or drinking in class, making offensive remarks, reading newspapers, sleeping or engaging in any other form of distraction. Inappropriate behavior in the classroom shall result in, minimally, a request to leave class.”

ADA Requirements. Classroom accommodations will be made for students with disabilities, if requested.

Religious Holidays. A student who intends to observe a religious holy day should make that intention known to the instructor prior to an absence. A student who is absent from classes for the observance of a religious holy day shall be allowed to take an examination or complete an assignment scheduled for that day within a reasonable time after the absence.

References:

SAS Certificate Exams:

· SAS Certified Base Programmer for SAS 9

· SAS Certified Advanced Programmer for SAS 9

· SAS Certified Predictive Modeler Using SAS Enterprise Miner 5