This webpage supports an entry in a Mathematical game. Work was conducted as part of MATH 5530 Statistical Computing. Files provided as sage worksheets can be run using the Sagemath Cloud.
| Type | File | Description |
|---|---|---|
| Talk | Playing a Game in Statistical Computing | Slides (.pdf) from a colloquium talk about the class and game. |
| Result | Results and Comments (local copy) | The results of the game (.pdf). (We won in the "group" category.) |
| Entry | Avoid Fines by Warming-Up the Machines | The submitted entry (.pdf). |
| Game Specifications | ||
| Checking an Industrial Process (local copy) | Description of the game (.pdf). | |
| Data spreadsheet (local copy) | Data spreadsheet (.xls) provided with the game. | |
| Destructive.data | The Destructive testing tab in the data spreadsheet, reformatted for import to R. | |
| NonDestructive.data | The Non-Destructive testing tab in the data spreadsheet, reformatted for import to R. | |
| Sage Worksheets | ||
| Ni_dependency.sagews | Determines the formula for Ni given \((d,c,x,y,z)\). | |
| Cr_dependency.sagews | Determines the formula for Cr given \((d,c,x,y,z)\). | |
| MC_totalfine.sagews | Does a straightforward but slow Monte Carlo simulation. | |
| count_analytic_fastMC.sagews | Counts violations of the specifications in each cylinder and uses them to estimate the expected fine using a simplified sampling and using a faster Monte Carlo simulation. | |
| figuremaker.sagews | Produces the figures used in the submission. |