Guolin Lai

DSC8240 Course Web

 
Business Modeling for Decision Support

Personal Statement
Chapter 1 Summary
Chapter 2 Report
    Breakeven Analysis
    Price & Demand Relationship
    Quantity Discounts Decision
    Hedging Investment Risk
    Time Value of Money
Enterprise DSS
Time Series Forecasting
DSS Development Project
Simulation Model Examples
    Government Contract Bidding
    GFAuto Model
    Customer Loyalty
    Game of Craps
Monte Carlo Simulation
Optimization Modeling
Term Project
Business Intelligence Research
 
Estimating the Probability of Winning at Craps

Background
Objective Hierarchies
Variables and Attributes
Influence Diagram
Mathematical Representation
Testing and Validation
Implementation and Use

Background

Joe Gamble loves to play craps at the casinos. He suspects that his chances of winning are less than 50-50, but he figures that he can at least play for quite a while before losing all of his money.

Objective

Assuming that Joe starts with %50 and each bet is worth $5, he wants to know whether he can play 100 games without going broke.

Variables and Attributes

Variable
Variable Type
How Measured
Related to
Probability of winning Input Variable % Win the toss or not
Random number Input Variable % Win the toss or not
Initial wealth Input Variable Amount in $ Wealth after each toss
Bet on each game Input Variable Amount in $ Wealth after each toss
Maximum no. of games Input Variable Integer Went broke or not

Influence Diagram

Mathematical Representation

Please refer to the Excel demo for details.

Testing and Validation

Implementation and Use

The model can be manipulated in Microsoft Excel.
Please click here to view the Excel Model.