Spreadsheet Modeling and Simulation
Topics: Simulation, Microsoft Excel, Spreadsheet, Computer simulation, Decision theory, Model / Pages: 6 (1490 words) / Published: Mar 29th, 2014

Krannert Graduate School of Management
Purdue University

MGMT 57000
SPREADSHEET MODELING AND SIMULATION

Spring 2014

Instructor: Yanjun Li, office: KRAN 422, phone: 494-4525, e-mail: li14@purdue.edu

Office Hours: Tuesday 1:00 – 4:00 pm, or by appointment.

Course Packet: The course packet contains cases and readings from various sources.

Textbook: David Hartvigsen, SimQuick: Process Simulation with Excel, 2nd Edition, Prentice Hall, 2004. (ISBN: 0-13-107880-1)

References: Law, A. M. and W. D. Kelton, Simulation Modeling and Analysis, 3rd Edition, McGraw Hill, 2000.

Luenberger, D. G., Investment Science, Oxford University Press, 1998.

Winston, W. L., Simulation Modeling Using @RISK, Duxbury, 2001.

Computer Software: Palisade Decision Tools, including @RISK, RISKOptimizer, and StatTools, are available in the computer labs in the Krannert building and Rawls Hall. A student version of the software and the installation guide can be downloaded for free at https://intra.krannert.purdue.edu/admin/kcc/Pages/Resources.aspx. SimQuick is included in the companion CD of our textbook.

Course Prerequisites: MGMT 67000

COURSE DESCRIPTION

In the past twenty years, Excel spreadsheets have become the standard tool that business people use to model and analyze quantitative problems. The latest versions of these spreadsheet packages contain powerful analytical tools that could be possible only with mainframe computers and mathematically trained personnel two decades ago. This course covers up-to-date and practical spreadsheet modeling and simulation tools that can be applied to a wide variety of business problems in finance, marketing, and operations.

The topical coverage mainly consists of the following four modules: (1) data analysis techniques to find the most likely description of the uncertainty in future business; (2) deterministic and stochastic optimization techniques to determine the best managerial



References: Law, A. M. and W. D. Kelton, Simulation Modeling and Analysis, 3rd Edition, McGraw Hill, 2000. Luenberger, D. G., Investment Science, Oxford University Press, 1998. Winston, W. L., Simulation Modeling Using @RISK, Duxbury, 2001.

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