7th Annual International Conference on Industrial Engineering and Operations Management

Statistical JAVA Gaming Simulation

Timothy Liu, Mason Chen & Joseph Jang
Publisher: IEOM Society International
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Track: High School STEM Project Presentation
Abstract


Team has designed a special game on which we apply Statistics, Probability, and Java to simulate each game move and predict the winning scenario. We applied binomial probability distribution to build a predictive model that could simulate the gaming sequence between two players. The sample size was determined based on two hypotheses: (1) playing sequence and (2) winning patterns. In this project, we identified four winning patterns and used Java to code these patterns and determine the gaming sequence and consequence based on conditional probability. The Java results were then compared to the Predictive Model to conduct objective root cause analysis for further improvement and optimization.  Human behavior was also considered to study the beginner level to the more advanced level. Based on the 2-Proportions Tests, team has achieved > 95% confidence that the optimum model can accurately predict the gaming sequence and winning probability which are verified and validated by Java simulation.  Team has been through a systematic problem solving process, and typical Team Building Cycle (Forming, Storming, Norming, and Performing). This is a good STEM Project for teaching kids on learning and applying Statistics, Java Programming, Problem Solving, and Team Building Dynamics.

Published in: 7th Annual International Conference on Industrial Engineering and Operations Management, Rabat, Morocco

Publisher: IEOM Society International
Date of Conference: April 11-13, 2017

ISBN: 978-0-9855497-6-3
ISSN/E-ISSN: 2169-8767