User Tools
milestone_4
Differences
This shows you the differences between two versions of the page.
|
milestone_4 [2023/03/20 14:46] scott [Procedure] |
milestone_4 [2024/03/22 17:52] (current) scott [Test and Pass Off] |
||
|---|---|---|---|
| Line 21: | Line 21: | ||
| Finally, as a group you will subject your system to a series of statistical distance measurements. | Finally, as a group you will subject your system to a series of statistical distance measurements. | ||
| - | You will need a microSD card for this task. Make sure that it is class 10 or above and has a capacity of at least 8 GB. The shop should have some of these for sale. If not, the bookstore or Amazon are good options. | + | You will need a microSD card for this task. Make sure that it is class 10 or above and has a capacity of at least 8 GB, but not more than 32 GB. The shop should have some of these for sale. If not, the bookstore or Amazon are good options. |
| ---- | ---- | ||
| Line 125: | Line 125: | ||
| - As you may recall from STAT 201, the maximum likelihood estimate of a probability is simply the ratio of successful trials to the number of total experiments. | - As you may recall from STAT 201, the maximum likelihood estimate of a probability is simply the ratio of successful trials to the number of total experiments. | ||
| - Calculate the 95% confidence intervals for each of your estimated probabilities. | - Calculate the 95% confidence intervals for each of your estimated probabilities. | ||
| - | - For help see this [[https://youtu.be/gClMYzniK3M| video]]. | ||
| - Remember from STAT 201, if all of you were to run the same experiment to estimate a probability p, and then calculate confidence intervals at the 95% level for your estimate, we would expect 95% of you, on average, to actually bound the true value of p within your upper and lower bounds of the confidence interval. See Section 5.2 (pp. 338-344) of your STAT 201 textbook for a reference. Given a desired width of your confidence interval, and no knowledge of p, Example 5.14 may be useful in determining the value of n you require. Use a 95% confidence interval for your calculations. | - Remember from STAT 201, if all of you were to run the same experiment to estimate a probability p, and then calculate confidence intervals at the 95% level for your estimate, we would expect 95% of you, on average, to actually bound the true value of p within your upper and lower bounds of the confidence interval. See Section 5.2 (pp. 338-344) of your STAT 201 textbook for a reference. Given a desired width of your confidence interval, and no knowledge of p, Example 5.14 may be useful in determining the value of n you require. Use a 95% confidence interval for your calculations. | ||
| - Notice that the width (difference between upper and lower bounds) of the confidence interval shrinks as n grows. This matches our intuition that more data will result in better estimates. | - Notice that the width (difference between upper and lower bounds) of the confidence interval shrinks as n grows. This matches our intuition that more data will result in better estimates. | ||
| - Produce a table summarizing your results. Include the value of n, the number of successful trials at each distance, your estimates of the probabilities p<sub>20</sub>, p<sub>40</sub>, and p<sub>60</sub>, and the 95% confidence intervals for each estimate. | - Produce a table summarizing your results. Include the value of n, the number of successful trials at each distance, your estimates of the probabilities p<sub>20</sub>, p<sub>40</sub>, and p<sub>60</sub>, and the 95% confidence intervals for each estimate. | ||
| - | - Compare your confidence intervals with data from another team. You can just use their computed confidence intervals directly, you don't need to recompute confidence intervals on their raw data. | + | - Compare your confidence intervals with data from another group. You can just use their computed confidence intervals directly, you don't need to recompute confidence intervals on their raw data. |
| - Answer these questions: is one system better for all distances? Or, does the answer to this question depend upon the distance, e.g., is one system better at 20 feet and the other system better at 40 feet? | - Answer these questions: is one system better for all distances? Or, does the answer to this question depend upon the distance, e.g., is one system better at 20 feet and the other system better at 40 feet? | ||
| Line 141: | Line 140: | ||
| - Show that the 'Hit Indicator LED' on the board and top of the gun comes on for target kit 2 | - Show that the 'Hit Indicator LED' on the board and top of the gun comes on for target kit 2 | ||
| - Verify that gun 2 cannot be hit by an opponent when the 'Hit Indicator LED' is on | - Verify that gun 2 cannot be hit by an opponent when the 'Hit Indicator LED' is on | ||
| - | - Verify that hits can be reliably detected when the kits are at least 40 feet apart. | + | - Verify that hits can be reliably detected when the kits are at least 40 feet apart |
| - Demonstrate that there are no false positives | - Demonstrate that there are no false positives | ||
| - Point gun 2 at the room lights and demonstrate that hits are not recorded | - Point gun 2 at the room lights and demonstrate that hits are not recorded | ||
milestone_4.1679345203.txt.gz ยท Last modified: 2023/03/20 14:46 by scott
Page Tools
Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Share Alike 3.0 Unported
