Exam 1
January 30, 2016
[highlight color=”options: yellow, black”]Exam 1 on Wed, Feb 17[/highlight]
Part 1:
Students will analyze agricultural commodity price data (link to Sheets data*). The data include monthly prices going back to 1960 for seven agricultural commodities, including corn, soybeans, wheat, calves, cattle, hogs and milk.
Each student has been randomly assigned 3 commodities (see Commodity Assignments below). For each assigned commodity students will (1) build a time series forecasting model using regression analysis; (2) prepare a graphic to illustrate data and model; (3) generate 8 price forecasts for March, June, September, December 2016 and 2017; and (4) write a paragraph describing your analysis and forecasts.
What to bring on Exam day:
- 1-page analysis for each assigned commodity (3 pages total).
- All activities and assignments printed, organized and neatly bound (paper clips, no staples).
- Exam is open book, open note, open calculator. Bring what you’ll want to use.
Part 2:
The in-class exam will be a combination of problem solving and short essay questions. All material covered since the beginning of term is fair game. We will have a review session during class on Mon, Feb 15.
Commodity Assignments:
Look up your 3 commodities corresponding to your PID (last 4 digits) in the table below.
- Corn
- Soybeans
- Wheat
- Calves
- Cattle
- Hogs
- Milk
Use the list above to determine your assignments. For example, if you see 1, 3 and 5 next to your 4-digit PID then you’ve been assigned Corn, Wheat and Cattle. Or, if you see 2, 4, 6 then you’ve been assigned Soybeans, Calves and Hogs. Etc.
PID4 | Data 1 | Data 2 | Data 3 |
0398 | 3 | 2 | 4 |
0460 | 5 | 7 | 6 |
0488 | 6 | 7 | 5 |
0558 | 3 | 5 | 6 |
0813 | 4 | 5 | 3 |
0882 | 7 | 1 | 5 |
1005 | 3 | 4 | 1 |
1025 | 4 | 5 | 3 |
1241 | 2 | 3 | 5 |
1347 | 5 | 4 | 2 |
1348 | 5 | 6 | 1 |
1516 | 3 | 2 | 4 |
1637 | 2 | 1 | 3 |
1650 | 6 | 1 | 7 |
1680 | 7 | 5 | 1 |
1720 | 3 | 2 | 6 |
1903 | 4 | 5 | 6 |
1917 | 1 | 5 | 4 |
1922 | 6 | 3 | 7 |
1938 | 6 | 4 | 7 |
1943 | 7 | 5 | 3 |
2271 | 6 | 7 | 1 |
2284 | 6 | 5 | 4 |
2407 | 2 | 1 | 6 |
2409 | 2 | 3 | 1 |
2431 | 6 | 3 | 1 |
2583 | 2 | 7 | 4 |
2704 | 5 | 7 | 2 |
2951 | 6 | 5 | 4 |
2995 | 2 | 3 | 7 |
3275 | 3 | 1 | 2 |
3547 | 4 | 7 | 5 |
3772 | 7 | 1 | 3 |
3778 | 3 | 7 | 5 |
4096 | 5 | 4 | 1 |
4212 | 2 | 3 | 5 |
4289 | 5 | 2 | 1 |
4443 | 1 | 2 | 4 |
4673 | 3 | 2 | 4 |
4735 | 4 | 7 | 1 |
5118 | 7 | 2 | 1 |
5160 | 3 | 7 | 2 |
5210 | 2 | 4 | 5 |
5303 | 3 | 1 | 7 |
5484 | 5 | 3 | 7 |
5679 | 3 | 4 | 7 |
6122 | 1 | 6 | 5 |
6129 | 2 | 5 | 1 |
6243 | 5 | 2 | 6 |
6253 | 2 | 1 | 7 |
6261 | 2 | 1 | 3 |
6274 | 6 | 1 | 2 |
6383 | 6 | 7 | 5 |
6634 | 3 | 6 | 1 |
6880 | 3 | 7 | 1 |
7003 | 5 | 1 | 4 |
7097 | 5 | 1 | 6 |
7191 | 4 | 6 | 7 |
7201 | 5 | 6 | 4 |
7230 | 7 | 2 | 4 |
7253 | 4 | 7 | 3 |
7277 | 4 | 1 | 5 |
7351 | 5 | 6 | 7 |
7390 | 5 | 1 | 2 |
7444 | 1 | 3 | 4 |
7459 | 3 | 5 | 1 |
7497 | 5 | 2 | 7 |
7568 | 3 | 6 | 2 |
7763 | 5 | 3 | 2 |
7832 | 5 | 7 | 2 |
8154 | 6 | 7 | 4 |
8200 | 5 | 6 | 4 |
8287 | 4 | 7 | 5 |
8350 | 7 | 3 | 1 |
8542 | 6 | 7 | 2 |
8613 | 7 | 6 | 5 |
8746 | 4 | 7 | 5 |
8955 | 2 | 6 | 7 |
8962 | 5 | 7 | 2 |
9100 | 5 | 6 | 2 |
9178 | 1 | 6 | 7 |
9205 | 1 | 7 | 2 |
9218 | 5 | 7 | 6 |
9220 | 5 | 1 | 3 |
9256 | 6 | 7 | 2 |
9322 | 1 | 2 | 3 |
9380 | 1 | 3 | 4 |
9535 | 1 | 5 | 7 |
9556 | 3 | 1 | 2 |
9637 | 3 | 4 | 1 |
9740 | 1 | 7 | 2 |
9829 | 3 | 5 | 4 |
9963 | 6 | 4 | 2 |
* Data Source: University of Illinois farmdoc project
2 Comments
[…] Previous postNext post […]
[…] Exam 1 Part 1 (take-home) Questions […]