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. |