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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City University of Hong Kong Information on a Course

offered by Department of Management Sciences with effect from Semester A in 2014/ 2015 Part I

Course Title: Business Modeling with Spreadsheets Course Code: MS3261

Course Duration: One Semester Credit Units: 3

Level: B3

Medium of Instruction: English Prerequisites: Nil

Precursors: Nil

Equivalent Courses: Nil

Exclusive Courses: CB2011 Solving Business Problems with Spreadsheet Modeling Part II

Course 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.

Course Intended Learning Outcomes (CILOs)

(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. CILOs Weighting DEC-related

dimension 1 understand managerial problems, collect relevant data, and

analyse the data 20% Ability

2 build sound models for the managerial problems using

spreadsheets 30% Ability

3 select appropriate solution method and implement the

analysis for the spreadsheet models 30% Accomplishment validate the results obtained from spreadsheet models, and

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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. TLAs 1, 2, 3

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.

1, 2, 3

2. Computer-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.

1, 2, 3, 4

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.

Constructive alignment of CILOs and TLAs TLA

1 TLA 2 TLA 3

CILO 1   

CILO 2   

CILO 3   

CILO 4 

Assessment Tasks/Activities

(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.

Types of Assessment Tasks (ATs)

Assessment Details Weighting

1, 2, 3

1. Written examination (two hours)

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.

40%

1, 2, 3 2. Homework Assignment

The homework assignments are designed to help students practise their problem-solving skills and obtain hands-on experience using spreadsheet modeling tools.

30%

1, 2, 3,

4 3. Project

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.

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Grading of Student Achievement: Refer to Grading of Courses in the Academic Regulations (Attachment) and to the Explanatory Notes.

Group Project Letter Grade

Grade Point Grade Definitions A+ A A- 4.3 4.0 3.7

Excellent: Strong evidence of original thinking; good organization, capacity to analyse and synthesize; superior grasp of subject matter; evidence of extensive knowledge base and familiarity with literature. Clearly and correctly states most critical points and important findings of the project. Excellent presentation skills. B+ B B- 3.3 3.0 2.7

Good: Evidence of original thinking, some evidence of critical capacity and analytic ability; reasonable understanding of issues; evidence of familiarity with literature. Clearly and correctly states some critical points and important findings of the project. Good presentation skills. C+ C C- 2.3 2.0 1.7

Adequate: Little evidence of original thinking, little evidence of critical capacity and analytic ability; reasonable understanding of issues. Correctly 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. Below 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 Grade

Grade Point Grade Definitions A+ A A- 4.3 4.0 3.7

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- 3.3 3.0 2.7

Good: Evidence of grasp of subject, some evidence of critical capacity and analytic ability; reasonable understanding of issues; evidence of familiarity with

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C+ C C-

2.3 2.0 1.7

Adequate: 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 literature.

Written Examination Letter

Grade

Grade Point Grade Definitions A+

A A-

4.3 4.0 3.7

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-

3.3 3.0 2.7

Good: Evidence of grasp of subject, some evidence of critical capacity and analytic ability; reasonable understanding of issues; evidence of familiarity with literature.

C+ C C-

2.3 2.0 1.7

Adequate: 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 literature.

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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 Basics

Introduction of Excel features and functions, such as Data/Sort, Functions, Tools, Macros, Add-in, 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 Contingent Analysis

Decision tree diagram. Structural “what-if” analyses. “So-what” analyses. Sensitivity analysis. Interpretation of results.

Risk Analysis through Excel Simulation

Basic terminologies of Excel simulation. Random number and random variate generation. Commonly used probability distributions (uniform, triangular, binomial, normal, …). Histogram. A profit calculation problem. Crystal ball basics. Applications in finance, marketing and operations management.

Textbook

Stephen G. Powell and Kenneth R. Baker. Management Science: The Art of Modeling with Spreadsheets, 2nd Edition, John Wiley & Sons, 2009.

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References