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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 % 1 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 2 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. 3