Question 1(1 point)

Simple decision problems that do not involve dependent decisions over time (single stage) can be portrayed as a decision tree or a payoff table.

Question 1 options:

True

False

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Question 2(1 point)

The values in the table correspond to the Profit(in thousands of dollars)that will be earned by a ski-apparel company based upon the size of their initial order for raw materials: They can place a small, medium or large order. The profits will vary depending on the amount of snow that actually falls during the selling season. Snowfall has been categorized as heavy, normal or light. The company is very thrifty in terms of spending money on analysis and therefore always delete dominated decision alternatives before conducting additional analysis. From the table, it is clear that one of the three decision alternatives is dominated and can be removed from further consideration.

Question 2 options:

True

False

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Question 3(1 point)

In decision analysis when probabilities associated with future states of nature are available we are able to calculate expected values. One interesting calculation in these problems is the Expected Value of Perfect Information (EVPI). Once calculated, the EVPI can be thought of as an upper bound on the amount the decision maker should be willing to pay on any information about the likely future states of nature.

Question 3 options:

True

False

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Question 4(1 point)

A utility function can be used to transform monetary payoffs into corresponding utility values that encorporate the decision makers attitude towards risk.

Question 4 options:

True

False

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Question 5(1 point)

In the sensitivity report associated with the optimal solution for a well formulated linear programming problem, the reduced cost for one of the decision variables is $2.33. From this information we can deduce that in the optimal solution for this problem the value for this same decision variable is zero.

Question 5 options:

True

False

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Question 6(1 point)

Consider the feasible region for a maximization linear programming problem with two decision variables depicted above. The optimal solution will

Question 6 options:

uniquely occur at the corner point in the top left corner of the feasible region (approximately at E=2, F=9).

be along one of the edges between two corner points.

be at a point that is interior to the feasible region.

be impossible to determine without knowing the slope of the objective function.

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Question 7(1 point)

The image above is the solver solution to a linear programming maximization problem. Which (if any) of the three constraints has slack?

Question 7 options:

lathe

finishing

# blocks

None of the constraints have slack.

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Question 8(1 point)

In a profit maximizing linear programming sensitivity report, the "shadow price" associated with a constraint is:

Question 8 options:

A)	The net $ effect per unit increase in the right hand side (RHS) of the constraint within the range of allowable changes.

B)	The per unit cost associated with forcing a non-binding constraint to become binding.

C)	The amount still available if the constraint is non-binding.

D)	None of the above.

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Question 9(1 point)

The above sensitivity report was created from the optimal solution of a maximization linear programming problem. Below are a list of possible management decisions associated with this problem. Assuming your objective remains to maximize profit and you can only implement one of the changes listed, which one of the decisions below would you recommend?

Question 9 options:

Force the production plan to include some boards so as to reduce the cost.

Add 2 hours of finishing time to the finishing constraint.

Add 10 hours of lathe time to the lathe constraint.

Add an additional 10 blocks to the # blocks constraint.

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Question 10(1 point)

We discussed three versions of probability during session 5. Which version would you attribute to this statement:

"Probability is a state of mind, a statement about the degree of belief that one has about likelihood of occurrence."

Question 10 options:

Newtonian

Bayesian

Frequentist

Classical

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