1. Simulation and Analysis of a Golf Course Sarah Daugherty MSIM 852 December 3, 2007

2. Simulated System Dynamics  9 hole course  Tee times: exp(11) minutes  Since golfers can begin to play a hole before the golfers in front of them finish it, each hole divided into parts: Tee Fairway (Par 3 = 0; Par 4 = 1; Par 5 = 2) Green  USGA averages for pace of play Par 4 = 15 minutes for group of 3 to 4 golfers

3. Implementation  Arena  Lessons learned: Golf course modeling is complicated since players can start before others are finished on the same hole.  Next time: Gather actual waiting times for each hole and fit to a distribution.

4. Results  40 Replications  Average course waiting time: 11.08 minutes  Average number of players per day: 44

5. Analysis: Confidence Interval 

6. Analysis: Autoregressive

7. Analysis: Batch Means  Batches of size 5  Batches of size 10 Rule: As batches become large, all correlation between them disappears.--Not what my data shows??

8.  Tee 1  Y = exp(0.1)  Y does not explain X because:  We expect: Analysis: Control Variates

9.  Introduced new system with tee times exp(9) minutes.  F-crit not very big implies treatments are similar, not different, except for number out. Analysis: ANOVA

10. Analysis: Paired Samples  Confidence interval shrinks for 11-9 Paired.  With identical sigma's, 11-9 Paired CI endpoints are the same. DR. BAILEY: Tried to use Behrens- Fischer…I’m having a hard time figuring it out because I don’t have anything like the “league” in the football.xls example to compare with tee time 11 or tee time 9.

11. Questions/Discussion