Assessment of B215 (Quantitative and Qualitative Analysis) and
B260 (Managerial Decision Analysis)
Fall, 2006
Learning Objectives for These Courses
An understanding of:
1. Decision analysis methods including decision trees, expected value, risk and uncertainty, and the value of information.
2. Forecasting methods including time series analysis, basic statistics, and regression analysis.
3. Linear programming techniques including graphical and computational approaches.
4. Other analytical tools including simulation, queuing, and game theory.
Assessment of Learning Objectives
Explanation of Test
Students in Bus 260 and 215 (MBA-One cohort course equivalent) were given a test composed of standardized questions drawn from the textbook test bank, created by the instructor, or drawn from certification exams such as the C.M.A. (Certified Management Accountant) exam. Exam questions and solutions are included in the appendix. The questions focused on the Decision
Analysis and Linear Programming learning objectives. Students are introduced to this material in the textbook, from lecture and example test problems.
Results for Fall, 2006
Exceptional: 19
Acceptable: 41
Unacceptable: 6
Results were assessed as follows: Exceptional, no errors in the answer to 15 questions; acceptable, from 82 to 99 percent of total points; unacceptable, below 82 percent of total points.

Appendix: Questions with Answers Used for Assessment
1. A manufacturer must decide whether to build a custom order or to contract it out at a cost of
$18. The custom order will be sold for $20. In-house manufacturing involves direct costs for materials of $3. The first step in manufacturing costs $5 and there is 20% chance that this step will not be completed satisfactorily. If the first step fails, there will not be sufficient time to start work again, but there will still be a choice of turning down the order or contracting out the project. If the project is contracted out at this time, there is a 20% chance of being too late and having to dump the final product.
The last stage of in-house processing can be a cheap but chancy process costing $3 that has a
10% chance of failing. At that point it would be too late to go to an outside contractor and all the previous work would be useless. The expensive process for the last stage of in-house processing always works, but it costs $6. a. Construct the decision tree diagram below illustrating the decision, showing net payoffs
and branch probabilities. b. Perform backward induction, what is the optimal course of action: c. What is the maximum expected payoff for this decision _____________

4. Preacher's blends two Scotch whiskies, light and dark. The ingredients include aged, fresh, and treated bases. Preacher's wants to use linear programming in determining what volume of each ingredient to mix in one batch each of the final products. This will be done in order to maximize total profit. Costs per liter are: aged--$5; fresh--$2; and treated--$6. Light Scotch sells for $10 per liter and dark for $8.
(a) Define the applicable variables for this problem with i = A, F, and T denoting aged, fresh, and treated bases and j = L, D denoting light and dark Scotch. Then express the linear programming objective in terms of these variables.
The following proportions of ingredient volumes contain agents for establishing taste.
Base Woodiness Bitterness Smoothness
Aged
Fresh
Treated
.05
.10
.05
.02
.04
.05
.20
.05
.10
Express each of the following constraints using the variables defined in (a).
(b) Woodiness agents in the light batch must be at least 7% of the total light Scotch volume.
(c) Bitterness agents in the dark batch cannot exceed 3% of the dark Scotch volume.
(d) Smoothness agents must be at least 12% of the total light Scotch volume.
(e) Smoothness agents cannot exceed 10% of the total dark Scotch volume. with i = A, F, and T denoting aged, fresh, and treated bases and j = L, D denoting light and dark Scotch we have X
AL
, X
FL
, X
TL
, X
AD
, X
FD
, and X
TD
.
Profit = Revenue

Cost
Revenue is: 10(X
AL
+ X
FL
+ X
TL
) + 8(X
AD
+ X
FD
+ X
TD
)
Cost is: 5(X
AL
+ X
AD
) + 2(X
FL
+ X
FD
) + 6(X
TL
+ X
TD
)
The objective is:Maximize P = 5X
AL
+ 8X
FL
+ 4X
TL
+ 3X
AD
+ 6X
FD
+ 2X
TD
(b) .05X
AL
+ .10X
FL
+ .05X
TL
> .07(X
AL
+ X
FL
+ X
TL
) or, .02X
AL

.03X
FL
+ .02X
TL
< 0
(c) .02X
AD
+ .04X
FD
+ .05X
TD
< .03(X
AD
+ X
FD
+ X
TD
) or,

.01X
(d) .20X
AL
+ .05X
FL
+ .10X
TL
> .12(X
AL
+ X
FL
+ X
TL
) or,

.08X
AD
+ .01X
FD
+ .02X
TD
< 0
AL
+ .07X
FL
+ .02X
TL
< 0
(e) .20X
AD
+ .05X
FD
+ .10X
TD
< .10(X
AD
+ X
FD
+ X
TD
) or, .10X
AD

.05X
FD
+ 0X
TD
< 0

5. Use the graphical procedure to determine the optimal solution to this linear program.
Minimize C = 3X1 – 2X2
Subject to: 5X1 + 5X2 > 25 (Resource A)
2X1 < 20 (Resource B)
X2 < 3 (Resource C)
3X1 + 9X2 < 36 (Resource D) where X1, X2 > 0
Draw a graph showing a) the feasible region b) the objective function c) the optimal solution d) calculate the optimal solution