A finished BUS-660 Topic 1 payoff table analysis example, with alternatives and states tabulated, expected value computed and the criterion itself examined. Searches like "bus 660 topic 1 assignment example", "bus660 topic 1 sample" and "bus-660 topic 1 example" land here.
What a finished BUS-660 Topic 1 payoff table analysis looks like
The finished example separates two things students merge, the alternatives a decision maker controls and the states of nature they do not. The table is built with one row per choice and one column per state, and every cell carries a payoff the reader can trace to an assumption. Expected value is computed across the states using stated probabilities, and the example says where those probabilities came from rather than treating them as given. It then compares the expected value criterion against the pessimistic and optimistic alternatives, and asks the question that matters commercially: whether a firm that would be ruined by the worst outcome should maximize the average at all.
How a BUS-660 Topic 1 example is structured
The example builds a table and then interrogates the rule applied to it. It opens with the decision, naming what is being chosen between and by when. A second section separates the controllable alternatives from the uncontrollable states and justifies the list of states as exhaustive. A third populates the payoffs, showing where each figure comes from. A fourth attaches probabilities to the states and reports their source, since assumed probabilities carry the whole calculation. A fifth computes expected value for each alternative and identifies the winner under that rule. A sixth applies the pessimistic and optimistic criteria and reports where they disagree. A closing section recommends a criterion for this firm, arguing from its size and its tolerance for a bad outcome.
Alternatives separated from states
What the decision maker controls and what happens to them are different columns, and merging them wrecks the table.
Payoffs traceable to assumptions
Every cell carries a figure a reader can follow back, rather than a number that appeared in the grid.
Probabilities given a source
Assumed likelihoods carry the entire expected value calculation, so where they came from is stated.
Criteria compared, not just applied
Expected value, pessimistic and optimistic rules are run against the same table and their disagreement reported.
A criterion chosen for this firm
A business that cannot survive the worst outcome should not maximize an average, and the paper argues the point.
Where marks go in BUS-660 Topic 1
Computing expected value and stopping is the standard shortfall, since the topic is about how a decision should be made and the arithmetic is the easy part. A second failure is probabilities inserted with no source, which makes the whole calculation an elaborate expression of a guess. Papers lose marks for states of nature that overlap or leave gaps, because the expected value is only meaningful if the states are mutually exclusive and cover everything. Recommending expected value for a firm that would be bankrupted by one of the outcomes ignores that averages apply over repetition and a company gets one attempt. Payoff figures given without a derivation leave nothing to verify, so a reader has no way to rely on the recommendation built from them.
Get a BUS-660 Topic 1 example written to your instructions
Send the BUS-660 Topic 1 problems and the rubric posted in your classroom, with the decision scenario your section supplied. We write a custom example to those criteria, with alternatives separated from states, payoffs traced to assumptions, probabilities sourced and the decision criterion itself argued, in 24 to 48 hours. The first is free.
BUS-660 Topic 1 questions, answered
When is expected value the wrong criterion?
When the decision happens once and one of the outcomes would end the business. Expected value describes what you would average over many repetitions, and a firm facing a single bet cannot rely on the average arriving. Where one branch is ruinous, a criterion weighted toward avoiding the worst case is more defensible, and saying so is what the topic is examining.
Where do the probabilities come from?
Historical frequency where the situation has recurred, published data where an external event is involved, or informed judgment where neither exists. All three are legitimate and they carry different weight, so name which you used. What is not defensible is a probability that appears in the table with no origin, since every conclusion afterward is a function of it.
How do I know my states of nature are complete?
They must be mutually exclusive and exhaustive, meaning exactly one will occur and no possibility is missing. Test it by asking whether any plausible future falls outside your columns, and whether two of them could happen together. Both failures break the expected value calculation, and the second is easier to commit than students expect when the states are described loosely.