Download BQM syllabus 2013

IMBA PROGRAM
COLLEGE OF COMMERCE
NATIONAL CHENGCHI UNIVERSITY
Business Quantitative Methods
Fall 2013
A. Instructor:
Office:
E-mail:
Phone:
Professor Kwei Tang
Dean’s Office, College of Commerce Building
[email protected]
2939-3091 ext. 88610
Class Hours: Thursday, 7:10-10:00 PM
Office Hours: Thursday, 6:10-7:00 PM and by appointments
B. Book, Course Materials, and Software
1. Textbook: Statistics for Business and Economics, 12th edition by D. R. Anderson,
D. J. Sweeney, and T. A. Williams, South-Western Publishing, 2014, 2012. ISBN:
0-285-17230-2, International Edition locally distributed by 滄海書局.
2. Class handouts – to be distributed.
3. Minitab (www.minitab.com), a commercial statistics package, and Excel add-ons
Solver will be used extensively.
C. Course Objectives
The course emphasizes applications through the use of case analysis/data sets and
presentations, and computer exercises. The focus of the course is as much on
modeling and presenting solutions to business problems as on understanding
statistical methods. Areas covered by the course include descriptive statistics,
exploratory data analysis, probability, decision analysis, estimation, hypothesis
testing, quality control, regression models, analysis of variance, and forecasting. At
the end of the course each student is expected to have
• A good understanding of several commonly used statistical techniques
in
business;
• The ability to model and solve business problems using statistical methods;
• The ability to give a non-technical presentation containing solutions, obtained by
statistical analysis of a data set from a business problem, to an audience of
managers/decision makers;
• A good understanding of how to use statistics software.
D. Grading Policy
• Homework assignments 10 %
• Cases 15 %
• Team and class participation 20 %
• Mid-term examination 20 %
• Final examination 35 %
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TENTATIVE CLASS SCHEDULE
Week Date
1
9/5
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
9/12
9/19
9/26
10/3
10/10
10/17
10/24
10/31
11/7
11/14
11/21
11/28
12/5
12/12
12/19
Topic
Text
Reading
Course Introduction and Descriptive
Statistics
Ch. 1, 2 & 3
Probability
No class
Discrete and Continuous Distributions
Sampling Distributions and Estimation
Hypothesis Testing
Decision Analysis
Mid-term Exam
Regression Analysis
Regression Analysis
Regression Analysis
Statistical Process Control
Analysis of Variance
Forecasting (time allows)
Questionnaire Design and Analysis
Final Exam
Ch. 4
1.2, 1.3, 2.1,
2.2, 2.3,
2.4,3.1,3.2,3.5
Ch. 4
Ch. 5 & 6
Ch. 7
Ch. 8 & 9
Ch. 21
5.1-5.4, 6.2
7.2 & 7.5
8.1-3, 9.1-4
Ch. 21
Ch. 14
Ch. 15
14.1-9
15.1-8
Ch. 19
Ch. 13
Ch. 17
19.1-2
13.1-3
Ch. 17
Ch. 12
12.1-3
Case and
Assignment
Case 1
Case 2
METHODS OF INSTRUCTION
The course is taught as a mix of lectures, case/data set presentations, class discussions,
interactive problem-solving, and computer exercises/demonstrations. Case/data set
analyses illustrate applications in diverse areas of management and provide opportunities
for the creative application of statistics to unstructured management problems.
Homework exercises emphasize the understanding of concepts and aim to develop
proficiency in translating business problems into statistical questions. Computer
exercises familiarize the students with statistical software for data analysis.
YOUR ROLE IN THE COURSE
Preparation
Each student is expected to be prepared for each class, to contribute to class discussions,
and to complete all assigned readings and exercises. The class will be divided into
several teams. All assignments will be handed in as a team. Class and team-work is
subject to the following rules:
-
if a team member does not contribute, then his/her name should not appear on the
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assignments handed in, and he/she must do the entire assignment and hand it in
separately;
-
active participation in class discussions and teams is encouraged and is viewed as
essential for clarifying difficult concepts. Thus, each team member will evaluate
his or her team members at the end of the course. Class and team participation
accounts for a total of 20% of the course grade.
Proficiency in working with data and statistical modeling can be attained only through
extensive practice with textbook problems and cases. We recommend that students
attempt the numerous exercises in the textbook on their own. Homework and case
assignments must be turned in on the specified due dates, except under extenuating
circumstances. All assignments are to be handed in on A4 papers, so as to minimize
misplaced assignments during grading. Furthermore, each assignment should be stapled
and legibly state the names of the participating members on the upper left hand corner of
the first page.
Two teams will be assigned to give case presentations. A team assigned to a case
presentation will not be required to turn in the corresponding case write-up. We suggest
that each case write-up not exceed six pages (four pages for the contents and two pages for
the attachments). A typical report contains at least the following sections: (1)
introduction and problem statement, (2) analysis: technical and non-technical, (3)
recommendations/action plans and suggestions for future study, and (4) all attachments
(graphs and tables, etc.).
Course Honor Policy
We expect and encourage students to discuss readings, case materials, and the concepts
covered by the course with one another. However, do not falsely represent someone else's
work as if it were your own. It is further expected that students will prepare case,
homework, or other assignments without the assistance or reference to students who have
taken the class before, prior semester's class notes and the like.
While working individually and with your team members,
make sure that you understand, in doing homework and case assignments, the
reason for choosing a particular technique, the mechanics of the solution procedure,
and the implication(s) of your final solution(s) and recommendations.
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