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EBGN 560 – Quiz #2 Freemark Abbey Winery Kristian Taylor Read the Freemark Abbey Winery case study by William Krasker ahead of time. Note that the only wine of interest in this situation is the Riesling; you may ignore the Cabernet Sauvignon and the Chardonnay. 1) Create a decision tree in Precision Tree that captures the situation being faced by William Jaeger of Freemark Abbey Winery. Strong recommendation: use range names and cell references; those are modeling best practices, and part of your grade concerns best practices. 2) Answer the following questions: a. What is the Expected Value (EV) of harvesting the grapes early? _____2.85__ b. What is the EV of leaving the grapes on the vine until after the rain hits (or doesn’t hit)? 3.75_ c. How low does the probability of rain have to be before Freemark Abbey should harvest the grapes early? Assume they are risk neutral, and will always choose the higher EV. ___ my tree doesn’t show a switch (I believe I built the tree wrong)_____ (hint: this is a tricky question) d. The case mentions that if rain occurs but botrytis does not form, the wine will be watery and will sell for less. It also mentions that in this case, Freemark could choose to sell the wine in bulk or sell the grapes directly, which would result in only half the revenue they would get for selling the watery wine, but would preserve their reputation for good wine. You can force a specific choice at a square decision node by right-clicking on the node, choosing Node Settings, and then checking one of the boxes under “Force.” In the situation where rain occurs but botrytis does not form, use the forcing option to model Freemark deciding to sell the wine in bulk (or the grapes directly – it has the same value). Given this decision, how high does the probability of rain have to be (to the nearest whole percent) before Freemark would choose to harvest the grapes early? Cannot figure out ____ e. Remove the “Force” from the decision node in question “d” by unchecking the box, so that Freemark is once again making that decision based on the higher EV. Also return the probability of rain to 50%, such that the tree is in its original state. Now suppose that, in the event that it does not rain, the probability of Low-Acid Wine goes up from 20% to 50%. What is the new EV of leaving the grapes on the vine? Cannot figure out Put your name where it says Your Name Here above, and add your name to the filename of this Word document and the filename of the Precision Tree file. Send both this Word document (with answers) and your decision tree (as a Precision Tree file) to me by 8:00 a.m. on Monday, February 12 th , 2024. Grading will be as follows: Is the tree structured correctly? (12 points) Are the input values correct? (8 points)
Is the tree easy to understand, run sensitivities on, and/or audit? (10 points) Were the questions above answered correctly? (2 points each) Maximum score: 40 points
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