City University of Hong Kong. Information on a Course offered by the Department of Management Sciences with effect from Semester A in 2012 / 2013

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1 Form 2B City University of Hong Kong Information on a Course offered by the Department of Management Sciences with effect from Semester A in 2012 / 2013 Part I Course Title: Quantitative Methods Course Code: MS5211 Course Duration: One Semester Credit Units: 3 Level: P5 Medium of Instruction: English Prerequisites: Nil Precursors: Nil Equivalent Courses: Nil Exclusive Courses: Nil Part II Course Aims This course aims to: Develop students ability to define, formulate, and model real world decision problems from an analytical point of view. Provide students with abilities to develop advanced quantitative skills. Course Intended Learning Outcomes (CILOs) Upon successful completion of this course, students should be able to: No. CILOs Weighting (if 1. Understand quantitative concepts that are important for practicing managers 2. Define decision problems, formulate and model the problems using quantitative skills studied; apply appropriate methodologies to find solutions and interpret the solutions found (Ability) 1

2 3. Handle computer software packages to solve the models built 4. Critically discuss academic literature and other information sources related to quantitative methods 5. Prepare reports integrating textual and numerical material and make effective oral communication using a range of traditional and electronic media; undertake a set of tasks associated with improving their career prospects Teaching and Learning Activities (TLAs) (Indicative of likely activities and tasks designed to facilitate students achievement of the CILOs. Final details will be provided to students in their first week of attendance in this course) CILO No. 1. Lecture TLAs Concepts and general knowledge of quantitative methods are explained. The relevant techniques are developed and applied in the context of real business situations. Examples are used to emphasize the crucial skills of describing and defining the problem before conducting any analysis. Whenever available, computer software packages are introduced as a tool for solving the model, so that students can actually bring what they learnt to their place of work. 2. Class discussion Hours/week (if Discussions on major issues related to quantitative methods. 3. Assignments Case assignment is used to provide training in analysing complex problem situations and solving business problems. Students are required to work in groups, observe existing practices and/or conduct research on related applications. They are expected to apply methodologies learned or design their solution to solve problems. Findings are presented in a report or through presentation, including a reflection upon their learning experiences and challenges. 2

3 Constructive Alignment of CILOs and TLAs TLA 1 TLA 2 TLA 3 CILO 1 CILO 2 CILO 3 CILO 4 CILO 5 Hours/week (if Assessment Tasks (Indicative of likely activities and tasks designed to assess how well the students achieve the CILOs. Final details will be provided to students in their first week of attendance in this course) CILO No. 1, 2, 3 & 5 1, 2, 3, 4 & 5 1, 2 & 5 Types of Assessment Tasks (ATs) 1. Written examination Assessment Details The examination is designed to assess students ability in problem formulation, model construction and development of a quantitative solution with logical interpretation. 2. Assignments Students work together to analyse business problems, research on similar problems, solutions and apply methodologies learned or design their own solution. The deliverable is a written report or presentation which includes a reflection upon their learning experiences and challenges 3. Test The test is designed to assess students ability in problem formulation, model construction and development of a quantitative solution with logical interpretation. Weighting (if 60% 30% 10% 3

4 Constructive Alignment of CILOs and Assessment Tasks AT 1 AT 2 AT 3 CILO 1 CILO 2 CILO 3 CILO 4 CILO 5 Grading of Student Achievement: Refer to Grading of Courses in the Academic Regulations for Taught Postgraduate Degrees. AT1: Written Examination Letter A+ A A- Point Definitions Excellent Strong evidence of original thinking; good organization, capacity to analyse and synthesize; superior grasp of subject matter; evidence of extensive knowledge base. B+ B B Good Evidence of grasp of subject, some issues; evidence of familiarity with C+ C C Adequate Student who is profiting from the university experience; understanding of the subject; ability to show some evidence of familiarity with D 1.0 Marginal Sufficient familiarity with the subject matter to enable the student to progress without repeating the course. F 0.0 Failure Little evidence of familiarity with the subject matter; weakness in critical and analytic skills; limited or irrelevant use of 4

5 AT2: Assignments Letter A+ A A- Point Definitions Excellent Strong evidence of understanding the key concepts and definitions of the learned subject; capacity to analyse and synthesize; superior grasp of subject matter; evidence of extensive knowledge base. B+ B B Good Evidence of grasp of subject, some issues; evidence of familiarity with C+ C C Adequate Student who is profiting from the university experience; understanding of the subject; ability to show some evidence of familiarity with D 1.0 Marginal Sufficient familiarity with the subject matter to enable the student to progress further. F 0.0 Failure Little evidence of familiarity with the subject matter; limited or irrelevant use of AT3: Test Letter A+ A A- Point Definitions Excellent Strong evidence of original thinking; good organization, capacity to analyse and synthesize; superior grasp of subject matter; evidence of extensive knowledge base. B+ B B Good Evidence of grasp of subject, some issues; evidence of familiarity with C+ C C Adequate Some evidence of grasp of subject, little issues. 5

6 D 1.0 Marginal Sufficient familiarity with the subject matter to enable the student to progress without repeating the case report. F 0.0 Failure Little evidence of familiarity with the subject matter; weakness in critical and analytic skills; limited or irrelevant use of Part III Keyword Syllabus 1. Introduction The concept of a system and a model. applications. Problem solving process. Quantitative models in business 2. Linear Programming Models Linear programming applications. Solving a linear program using the graphical method for two decision variables and computer packages (e.g., Excel) for two or more decision variables. Transportation, transshipment and assignment problems. 3. Queues Some queuing terminology. Modeling arrival and service processes. Birth-death processes. The balance equation method. M/M/1 queuing system. M/M/s queuing system. M/M/1 or M/M/s with a finite capacity. Economics of Queuing Systems. 4. Decision Making Under Uncertainties Decision tables. Value of information. Decision trees. Bayesian inference for categorical data analysis in decision trees. 5. Statistical Quality Control Process variation. Control charts for variables ( x, S and R charts). Control charts for attributes (p and c charts). 6

7 Recommended Reading Render, B., Stair, R. M. and Hanna, M. E. Quantitative Analysis for Management, 11 th edition, Pearson Education, 2012 Winston, W. L., Microsoft Excel 2010: Data Analysis and Business Modeling, Microsoft Press, 2011 (e-book) Keller, G., Statistics for management and economics, 9th edition, South-Western College Pub, Online Resources The Science of Better (website of success stories) Analytics (internet magazine) Statistics Glossary 7