Weekly Take-home

The fourteen regular software take-homes and the course synthesis submission.

Each regular take-home is one Excel workbook with three sheets: an Instructions tab with every step and why it matters, the model sheet where you do the work, and a Free responses sheet for your written answers plus the required AI-use disclosure (see Using AI).

The model is not built for you. Every model sheet works in the same four blocks:

  • A. Case brief: a short narrative and the raw figures, exactly as somebody in the case would hand them to you. Not every figure is one you need, and at least one arrives on the wrong basis or in the wrong unit.
  • B. Your model: before you compute anything, you define the quantities in words with their units, write the relationships or constraints you are going to use, and say which figures you left out and why. This block is where most of the thinking is.
  • C. Solve: the work area. Nothing here is pre-labelled with the answer’s shape.
  • D. Read the answer: the two or three numbers a decision-maker would actually act on.

You fill every red cell; plain cells are given. You submit the single completed .xlsx on Canvas. That one file is your entire regular-week submission, and it is due Sunday at 11:59 PM of that week. Every teaching week in Weeks 1–13 and 15 carries one, and the course synthesis closes the term as a bigger, choose-your-own submission with no starter workbook (announced in Week 12, due Sun Dec 13). Point values are in Grading.

Late work follows the 3-3-3 rule. The one trap worth naming here: if you think you’ll submit late, don’t upload a placeholder first, because your last on-time version is the one that gets graded.

Each row links to that week’s take-home; the starter file downloads from the lesson page.

Wk Weekly take-home (graded)
1 Break-even from a brief: classify the costs, chart it, then re-run it on what really happened
2 Probability from raw counts, put on the decision's own time basis, then EV, spread, and a price ceiling
3 Build the payoff table, work all five criteria, then find where Hurwicz changes its mind
4 Build the cost table: EV, EOL and the EVPI ceiling
5 Sequential tree: fold back, price the option, find the flip
6 Bayesian revision from counts, EVSI, and a utility re-fold
7 Formulate two LPs and enumerate every corner (no Solver)
8 Formulate an LP, wire up Solver, read the Answer Report
9 LP sensitivity: shadow prices, both ranges & reduced cost
10 Three network models with Solver: an unbalanced grid, matching & a hub
11 Weighted scoring, AHP consistency & preemptive goal programming
12 CPM / PERT from a narrative: critical path, risk & crashing
13 Choose the window and alpha: moving average vs smoothing
15 Linear trend and a negative-slope regression: R² & forecasts

Week 14 is Thanksgiving break and Week 16 is the synthesis presentations, so neither has a take-home.