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# QUESTION 1 Decision Analysis Guide to marks: 20 marks- 6 for a, 2 each for b1 & b2, 3 each for b3 & b4, 4 for b5 Show all calculations to support your answers. You may follow the methods shown in the...

QUESTION 1 Decision Analysis

Guide to marks: 20 marks- 6 for a, 2 each for b1 & b2, 3 each for b3 & b4, 4 for b5

You may follow the methods shown in the mp4 on Decision Analysis for a way to do part (b) of this question if you wish.

(a) Discuss the differences among decision making under certainty, under risk and under complete uncertainty.
(b) Bikram Shrestha is considering investing some money that he inherited. The following payoff matrix gives the profits that would be realised during the next year for each of the investments that Bikram is considering.

Good EconomyPoor Economy
Share market\$80,000(\$20,000)
Bonds30,00020,000
Real estate 25,00015,000

Answer the following questions. Each answer must be supported with appropriatecalculations and/or a table of figures, andyou must state for questions 1 to 4 which alternative would be selected.

1 Which alternative would an optimist choose?
2 Which alternative would a pessimist choose?
3 Which alternative is indicated by the criterion of regret?
4 Assuming probability of a good economy = 0.3 using expected monetary values what is the optimum action?
5 What is the expected value of perfect information?

QUESTION 2 Value of information

Guide to marks: 20 marks â€“ 4 for a, 8 for b, 2 for c, 6 for d

Show all calculations to support your answers. You may follow the methods shown in the mp4 on Value of info for a way to answer this question if you wish, but however you do the calculations you must specifically provide answers to the 4 questions.

DO NOT ROUND probability calculations with Round Function. You may display them to 2 decimal places if you like but do not round in memory.

Jerry is thinking about opening a bicycle shop. He can open a large shop (a1) or a small shop (a2). He believes that a large shop would earn a profit of \$80,000 if the market is good (s1) but would lose \$40,000 if the market is poor (s2). A small shop would return \$30,000 profit in a good market and a loss of \$10,000 in a poor market. Jerry believes that there is a 50-50 chance that the market will be good.

(a) What should Jerry do? Show calculations.

A friend would charge him \$3,000 for some market research providing.one of two signals, that the market is favourable or unfavourable. His past record is such that 80% of the time he would correctly provide a favourable market prediction when the market is good and 60% of the time he would correctly provide an unfavourable market prediction when the market is poor.

(b) Revise the prior probabilities in light of his friendâ€™s track record.

(c) What is the posterior probability of a good market given that his friend has provided an unfavourable market prediction?

(d) What is the expected net gain or loss from engaging his friend to conduct the market research? Should his friend be engaged? Why?

QUESTION 3 Monte Carlo Simulation

This is a work integrated assessment item. The tasks are similar to what would be carried out in the workplace.

Guide to marks: 20 marks â€“ 12 for a, 2 for b, 6 for c

Tully Tyres sells cheap imported tyres. The manager believes its profits are in decline. You have just been hired as an analyst by the manager of Tully Tyres to investigate the expected profit over the next 12 months based on current data.

â€¢ Monthly demand varies from 100 to 200 tyres â€“ probabilities shown in the partial section of the spreadsheet below.
â€¢ The average selling price per tyre follows a discrete uniform distribution ranging from \$60 to \$80 each. This means that it can take on equally likely integer values between \$60 and \$80 â€“ more on this below.
â€¢ The average profit margin per tyre after covering variable costs follows a continuous uniform distribution between 20% and 30% of the selling price.
â€¢ Fixed costs per month are \$1500.

(a) Using Excel set up a model to simulate the next 12 months to determine the expected average monthly profit for the year. You need to have loaded the Analysis Toolpak Add-In to your version of Excel. You must keep the data separate from the model. The model should show only formulas, no numbers whatsoever.

You can use this template to guide you:

Tully Tyres

DATA

 Prob Cum prob Demand Selling Price \$60 \$80 0.05 100 Monthly Fixed cost \$1,500 0.10 120 Profit Margin 20% 30% 0.20 140 0.30 160 0.25 180 0.10 200 1.00 MODEL Selling Profit Fixed Month RN 1 Demand Price RN 2 Margin Costs Profit

â€¢ The first random number (RN 1) is to simulate monthly demands for tyres.
â€¢ The average selling price follows a discrete uniform distribution and can be determined by the function =RANDBETWEEN(60,80) in this case. But of course you will not enter (60,80) but the data cell references where they are recorded.
â€¢ The second random number (RN 2) is used to help simulate the profit margin.
â€¢ The average profit margin follows a continuous uniform distribution ranging between 20% and 30% and can be determined by the formula
= XXXXXXXXXX)*the second random number (RN 2). Again you do not enter 0.2 and 0.3 but the data cell references where they are located. Note that if the random number is high, say 1, then XXXXXXXXXXbecomes 1 and when added to 0.2 it becomes 0.3. If the random number is low, say 0, then XXXXXXXXXXbecomes zero and the profit margin becomes 0.2.
â€¢ Add the 12 monthly profit figures and then find the average monthly profit.

Show the data and the model in two printouts: (1) the results, and (2) the formulas. Both printouts must show the grid (ie., row and column numbers) and be copied from Excel and pasted into Word. See Spreadsheet Advice in Interact Resources for guidance.

(b) Provide the average monthly profit to Tully Tyres over the 12-month period..

(c) You present your findings to the manager of Tully Tyres. He thinks that with market forces he can increase the average selling price by \$20 (ie range from \$80 to \$100) without losing sales. However he does suggest that the profit margin would then increase to range from 22% to 32%.

He has suggested that you examine the effect of these changes and report the results to him. Change the data accordingly in your model to make the changes and paste the output in your Word answer

Then write a report to the manager explaining your conclusions with respect to his suggestions. Also mention any reservations you might have about the change in selling prices.

The report must be dated, addressed to the Manager and signed off by you.
(Word limit: No more than 150 words)

QUESTION 4 Regression Analysis

Guide to marks: 20 marks â€“ 5 for a, 10 for b, 3 for c, 2 for d

Belinda, the accountant at Murray Manufacturing Company wants to identify cost drivers for support overhead costs. She has the impression that the staff spend a large part of their time ensuring that the equipment is correctly set up and checking the first units of production in each batch. Deborah has collected the following data for the past 12 months:

MonthOH CostMHBatches
1\$80,0002,200300
240,0002,400120
363,0002,100250
445,0002,700160
544,0002,300200
648,0003,800170
765,0003,600260
846,0001,800160
933,0003,200150
1066,0002,800210
Total

530,000

26,9001,980

(a) Using the high-low method to estimate support overhead costs based on machine hours, what would be the estimated support overhead costs (to the nearest \$) for a month in which 3,000 machine hours were used?

(b) Using Excel, perform three regression analyses to regress Overhead Cost against Machine Hours, then against Batches, then against both of them simultaneously. Paste your results into Word. State the cost equation from each. Analyse and comment on the results of each regression as you perform it and determine the best one to use as a basis for future use.

(c) If you had to settle for the results of a simple regression, which one would you use and why?

(d) Using the best regression result determine the projected Overhead Cost in a month in which there were 2000 machine hours worked and 150 batches produced.

QUESTION 5 CVP Analysis

Guide to marks: 20 marks â€“ 4 for a, 4 for b, 4 for c, 8 for d

A manufacturer can make two products, A and B. The following data are available:B

ProductABTotal
Sales price per unit\$10\$20
Variable cost per unit\$5\$12
Total fixed costs\$4,000

(a) Calculate the unit contribution margin for each product.
(b) This month the manufacturer will specialise in making only Product B. How many does he need to sell to break even?
(c) If they specialise in making only A what is the breakeven sales volume for the month in sales dollars?
(d) He now decides to manufacture both A and B this month in the ratio of 2 A to 1 of B.
(i) How many of each product must be sold to earn a profit of \$5,000 before tax for the month?
(ii) How many of each product must be sold to earn a profit of \$21,000 after tax (of 30c in the dollar) for the month?

END OF ASSIGNMENT 3

Rationale

This assessment task covers topics 3,4,5,6 and 8: Decision analysis and value of information, simulation, correlation and regression analysis and CVP analysis. Specifically, it seeks to assess your ability to complete the following subject learning outcomes:

• apply decision theory to business situations
• use simulation in complex decisions
• demonstrate understanding of the application of statistical hypothesis testing in regression analysis
• apply CVP analysis to product mix decisions involving single and multiple products
Answered Same Day Sep 18, 2019

## Solution

David answered on Nov 25 2019
QUESTION 1 Decision Analysis
Guide to marks: 20 marks- 6 for a, 2 each for b1 & b2, 3 each for b3 & b4, 4 for b5
You may follow the methods shown in the mp4 on Decision Analysis for a way to do part (b) of this question if you wish.
(a) Discuss the differences among decision making under certainty, under risk and under complete uncertainty.
The four criteria are
Â· Maximax
Â· Maximin
Â· Minimax regret
Â· Expected monetary value
Maximax is used by an optimistic decision maker. This criteria occurs when all things happens in the way the decision maker thinks and he wishes to maximize his profit
Maximin is used by a pessimistic decision maker. This criteria occurs when all things happens against the way the decision maker thinks and he wishes to minimize his loss
Minimax is based on the opportunity loss. Here, the decision maker first selects the maximum loss that he could incur his strategy and choose a minimum loss strategy to minimize his loss
(b) Bikram Shrestha is considering investing some money that he inherited. The following payoff matrix gives the profits that would be realized during the next year for each of the investments that Bikram is considering.

Good Economy
Poor Economy
Share market
\$80,000
(\$20,000)
Bonds
30,000
20,000
Real estate
25,000
15,000
Answer the following questions. Each answer must be supported with appropriate calculations and/or a table of figures, and you must state for questions 1 to 4 which alternative would be selected.
The table given below shows the workings of decision making
Â
Good Economy
Poor Economy
EMV
Row Min
Row Max
Probabilities
0.3
0.7
Â
Â
Â
Shares
80000
-20000
10000
-20000
80000
Bonds
30000
20000
23000
20000
30000
Real Estates
25000
15000
18000
15000
25000

Â
maximum
23000
20000
80000

Best EV
maximin
maximax
1 Which alternative would an optimist choose?
Maximax = Max (80000, 30000, 25000) = 80000
The decision is to invest in Shares
2 Which alternative would a pessimist choose?
Maximin = Max (-20000, 20000, 15000) = 20000
The decision is to invest in Bonds
3 Which alternative is indicated by the criterion of regret?
The criterion of regret is calculated by using the opportunity loss table and the output workings is given below
Â
Good Economy Regret
Poor Economy Regret
Maximum Regret
Expected Regret
Probabilities
0.3
0.7
Â
Â
Shares
0
40000
40000
28000
Bonds
50000
0
50000
15000
Real Estates
55000
5000
55000
20000
Minimax regret
Â
Â
40000
Â
From the above table, we see that the best alternative is Shares
4 Assuming probability of a good economy = 0.3 using expected monetary values what is the optimum action?
EMV (Shares) = 80000 * 0.3 â€“ 20000 * 0.7 = 10000
EMV (Bonds) = 30000 * 0.3 + 20000 * 0.7 = 23000
EMV (Real Estates) = 25000 * 0.3 + 15000 * 0.7 = 18000
On comparing the EMV values, we see that the best alternative is Bonds
5 What is the expected value of perfect information?
The expected value of perfect information is calculated by using the formula given below
EVPI = EV/PI â€“ EMV
The workings is given below
Â
Good Economy
Poor Economy
Maximum
Probabilities
0.3
0.7
Â
Shares
80000
-20000
Â
Bonds
30000
20000
Â
Real Estates
25000
15000
Â
Perfect Information
80000
20000
Â
Perfect*probability
24000
14000
38000
Best Expected Value
Â
Â
23000
Exp Value of Perfect Info
Â
Â
15000
The expected value of perfect information is (38000 â€“ 23000 = 15000) \$ 15000
QUESTION 2 Value of information
Guide to marks: 20 marks â€“ 4 for a, 8 for b, 2 for c, 6 for d
Show all calculations to support your answers. You may follow the methods shown in the mp4 on Value of info for a way to answer this question if you wish, but however you do the calculations you must specifically provide answers to the 4 questions.
DO NOT ROUND probability calculations with Round Function. You may display them to 2 decimal places if you like but do not round in memory.
Je
y is thinking about opening a bicycle shop. He can open a large shop (a1) or a small shop (a2). He believes that a large shop would earn a profit of \$80,000 if the market is good (s1) but would lose \$40,000 if the market is poor (s2). A small shop would return \$30,000 profit in a good market and a loss of \$10,000 in a poor market. Je
y believes that there is a 50-50 chance that the market will be good.
(a) What should Je
y do? Show calculations.
A friend would charge him \$3,000 for some market research providing. One of two signals, that the market is favorable or unfavorable. His past record is such that 80% of the time he would co
ectly provide a favorable market prediction when the market is good and 60% of the time he would co
ectly provide an unfavorable market prediction when the market is poor.
The decision table for the Je
y is given below
Â
Good Market
Poor Market
Large Shop
80000
-40000
Small Shop
30000
10000
The expected value for perfect information is given below
Â
Good Market
Poor Market
Maximum
Probabilities
0.5
0.5
Â
Large Shop
80000
-40000
Â
Small Shop
30000
10000
Â
Perfect Information
80000
10000
Â
Perfect*probability
40000
5000
45000
Best Expected Value
Â
Â
20000
Exp Value of Perfect Info
Â
Â
25000
The expected value of perfect information is \$ 25000
Therefore, Je
y can ask suggestions from his friend regarding whether the market is favorable or unfavorable
(b) Revise the prior probabilities in light of his friendâ€™s track record.
If the prior probabilities are P(H0) = P(HA) then the outcomes favoring H0 are those for which the posterior probability ratio...
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