City University of Hong Kong. Information on a Course offered by Department of Management Sciences with effect from Semester A in 2014/ 2015

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1 ity University of Hong Kong Information on a ourse offered by Department of Management Sciences with effect from Semester A in 2014/ 2015 Part I ourse Title: usiness Modeling with Spreadsheets ourse ode: MS3261 ourse Duration: One Semester redit Units: 3 Level: 3 Medium of Instruction: English Prerequisites: Nil Precursors: Nil Equivalent ourses: Nil Exclusive ourses: 2011 Solving usiness Problems with Spreadsheet Modeling Part II ourse Aims This course aims to develop students ability to formulate, analyse and solve business problems using spreadsheet modeling. Focus of the course is not about becoming a spreadsheet expert, but about modeling through speadsheets. The goal of the course is to train students to become effective modellers who can build sound models to solve business problems in various functional areas of business. ourse Intended Learning Outcomes (ILOs) (state what the student is expected to be able to do at the end of the course according to a given standard of performance) Upon successful completion of this course, students should be able to: No. ILOs Weighting understand managerial problems, collect relevant data, and analyse the data build sound models for the managerial problems using spreadsheets select appropriate solution method and implement the analysis for the spreadsheet models validate the results obtained from spreadsheet models, and communicate and explain the analysis and findings to nonspecialists DErelated dimension 20% Ability 30% Ability 30% Accomplishment 20% Accomplishment

2 Teaching and Learning Activities (TLAs) (Indicative of likely activities and tasks designed to facilitate students achievement of the ILOs. Final details will be provided to students in their first week of attendance in this course) ILO No., 4 TLAs 1. Lectures: In the lectures, students learn the concepts of modeling, formulation of managerial problems in various functional areas, and tools in spreadsheet modeling. They will be provided with opportunities for peer interactions in the lectures. 2. omputer-based laboratories: Hands-on experience with the techniques and problem solving activities based on real world business problems. The laboratory sessions consolidate and supplement what the students learn in lectures. 3. Group Project: Students work in small groups to solve particular business problems using spreadsheet modeling techniques and tools learned in the course. The project is designed to be a complete decision-making process, including data collection, problem formulation, modeling, analysis, solution methods with appropriate tools, and validation of the results. onstructive alignment of ILOs and TLAs TLA 1 TLA 2 TLA 3 ILO 1 ILO 2 ILO 3 ILO 4 Assessment Tasks/Activities (Indicative of likely activities and tasks designed to assess how well the students achieve the ILOs. Final details will be provided to students in their first week of attendance in this course) ILO NO., 4 Types of Assessment Tasks (ATs) 1. Written examination (two hours) 2. Homework Assignment 3. Project Assessment Details The examination covers all topics of the course. It is designed to assess students understanding on the concepts of spreadsheet modeling, and their ability to apply them to solve business problems. The homework assignments are designed to help students practise their problem-solving skills and obtain hands-on experience using spreadsheet modeling tools. Students work in small groups to produce a collaboratively written report. They need to document in a well-written report the details of the spreadsheet model of the business problem they choose, and deliver an oral presentation in the class. Weighting 40% 30% 30%

3 Grading of Student Achievement: Refer to Grading of ourses in the Academic Regulations (Attachment) and to the Explanatory Notes. Group Project Letter Point A+ 4.3 A 4.0 A base and familiarity with learly and correctly states most critical points and important findings of the project. Excellent presentation skills. Evidence of original thinking, some learly and correctly states some critical points and important findings of the project. Good presentation skills. Little evidence of original thinking, little issues. orrectly states some critical points and some of the findings of the project. Average presentation skills. D 1.0 Marginal: Very little evidence of original thinking, critical capacity, and analytic ability but shows marginal understanding of subject matters and issues and states a few critical points and findings of the project. elow average presentation skills. F 0.0 Failure: Very little evidence of familiarity with the subject matter and issues; weakness in critical and analytic skills. Poor presentation skills. Test Letter A+ A A- Point base. + Evidence of grasp of subject, some

4 + Some evidence of understanding of the subject; ability to perform basic statistical model building and data analysis for marketing research. D 1.0 Marginal: Adequate familiarity with the subject matter; shows marginal ability to perform basic statistical model building and data analysis for marketing research. F 0.0 Failure: Little evidence of familiarity with the subject matter; weakness in critical and analytic skills; limited or irrelevant use of Written Examination Letter A+ A A- Point base. + Evidence of grasp of subject, some + Some evidence of understanding of the subject; ability to perform basic statistical model building and data analysis for marketing research. D 1.0 Marginal: Adequate 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

5 Part III Keyword Syllabus Introduction to Spreadsheet Modeling Definition of modeling. Types of models. Modeling steps. A systematic approach (discover, diagnose, design and deliver) for exploratory spreadsheet modeling. Excel asics Introduction of Excel features and functions, such as Data/Sort, Functions, Tools, Macros, Addin, and Forms. Examples on the above features and functions. Data Analysis Features of data in business contexts. Approach to organizing data to support decision making. Extraction of useful information from available data. Visualization, database/list, searching and editing, sorting, filtering, tabulating (pivot table), importing data from files and the Internet, data table. Resource Allocation Introduction of resource allocation problems in different functional areas. Modeling and problem formulation. Excel solver setup. Model layout. Examples in finance including optimal risk-return portfolio, and capital budgeting. Examples in marketing including media planning, and sales force territory planning. Examples in operations management including production planning, and logistics and operations planning. Decision Tree Analysis and ontingent Analysis Decision tree diagram. Structural what-if analyses. So-what analyses. Sensitivity analysis. Interpretation of results. Risk Analysis through Excel Simulation asic terminologies of Excel simulation. Random number and random variate generation. ommonly used probability distributions (uniform, triangular, binomial, normal, ). Histogram. A profit calculation problem. rystal ball basics. Applications in finance, marketing and operations management. Textbook Stephen G. Powell and Kenneth R. aker. Management Science: The Art of Modeling with Spreadsheets, 2 nd Edition, John Wiley & Sons, 2009.