QMB 5311 - QUANTITATIVE METHODS IN BUSINESS (Fall 2005)
QMB 5311 - QUANTITATIVE METHODS IN BUSINESS (Fall 2005)
QMB 5311 - QUANTITATIVE METHODS IN BUSINESS (Fall 2005)
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<strong>QMB</strong> <strong>5311</strong> - <strong>QUANTITATIVE</strong> <strong>METHODS</strong> <strong>IN</strong> BUS<strong>IN</strong>ESS (<strong>Fall</strong> <strong>2005</strong>)<br />
CRN 17057 BUSN 307 6:00pm – 8:50pm R<br />
Instructor: Dr. Somnath Mukhopadhyay Phone: (915) 747-7720<br />
Office: BUSN 208 Fax: (915) 747-5126<br />
Office hours: 1:00p-3:00p (M, T, W) and 4:30p-6:00p (R) or by appointment.<br />
E-Mail: smukhopadhyay@utep.edu URL:http://faculty.utep.edu/smukhopadhyay<br />
COURSE DESCRIPTION (Graduate Catalog)<br />
Introduction to quantitative methods applied to business decision making. The course will focus<br />
on solution of business problems using quantitative methods that include probability theory and<br />
tests of hypotheses.<br />
GENERAL COURSE OBJECTIVES<br />
• Students will learn to build quantitative models for managerial decision making<br />
• Students will apply statistical and other quantitative methods to solve business problems<br />
• Students will learn to use <strong>QMB</strong> tools to solve and analyze business problems<br />
Students’ understanding of this course and ability to meet the above objectives will be measured<br />
by the course mid-term and final examinations. In-class and homework assignments will be used<br />
throughout the course to develop the students’ understanding and ability to meet the objectives.<br />
REQUIRED COURSE MATERIALS<br />
David R. Anderson, Dennis J. Sweeney, and Thomas A. Williams, Quantitative Methods for<br />
Business, Special Edition – ISBN: 0-324-33799-X<br />
COURSE PREREQUISITE<br />
<strong>QMB</strong> 2301 (Fundamentals of Business Statistics)<br />
ATTENDANCE<br />
Students are expected to attend classes regularly and on time. They should take full<br />
responsibility when they miss a class or come to a class late.<br />
EXAMS<br />
There will be 1 mid-term exam and a final examination. Final exam dates are on page 3.<br />
HOMEWORK<br />
Homework assignments (mostly based on problems in the textbook) are generally not to be<br />
submitted—unless otherwise announced in class beforehand. The assignments are intended to<br />
prepare students for examinations.
2<br />
COURSE GRAD<strong>IN</strong>G<br />
Midterm Exam<br />
Final Exam<br />
Project<br />
100 points<br />
100 points<br />
100 points<br />
Total Points earned: >= 270 >= 240 >= 210 >= 180
3<br />
COURSE SCHEDULE<br />
The instructor will attempt to adhere to the course schedule below, but does reserve the right to<br />
alter course content, class assignments and activities, and/or dates as deemed necessary.<br />
Weeks<br />
Aug 25<br />
Sep 1<br />
Topics<br />
Course Introduction.<br />
Chapter 1. Data and Statistics<br />
Chapter 2. Descriptive Statistics<br />
8 Chapter 3. Introduction to Probability<br />
15 Chapter 4. Probability Distributions<br />
22 Chapter 6 – Hypothesis Testing<br />
29 Chapter 8 – Linear Regression<br />
Oct 6 Exam 1.<br />
13 Chapter 9. Decision Analysis.<br />
20 Chapter 10. Forecasting.<br />
27 Chapter 11. Introduction to Linear Programming (LP)<br />
Nov 3<br />
Chapter 12 – Sensitivity Analysis<br />
10 Chapter 13 – LP Applications<br />
17 Chapter 14 – Transportation, Assignment, and Transshipment<br />
24 Thanksgiving holiday – no class.<br />
Dec 01<br />
Final<br />
Final Exam review<br />
Final Exam – Dec 08, 7:00pm - 9:45pm
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