Solved by verified expert:Assignment steps add 300 words to the attached case study. The section is probability of stock paragraph.also compute the information below in the attached spreadsheet.Compute the probability of a stock-out for the order quantities suggested by members of the management team (i.e. 15,000; 18,000; 24,000; 28,000).

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Order Quantity

Purchase Cost per unit

15,000

$ 16.00

Sales

Pessimistic

Likely

Optimistic

Order Quantity

Purchase Cost per unit

$

Order Quantity Total Cost

10,000

20,000

30,000

Pessimistic

Likely

Optimistic

10,000

20,000

30,000

18,000

18,000

18,000

$

$

$

288,000

288,000

288,000

Total Revenue @

$24.00

$ 240,000

$ 480,000

$ 720,000

20,000

$ 16.00

Pessimistic

Likely

Optimistic

Order Quantity Total Cost

10,000

20,000

30,000

20,000

20,000

20,000

$

$

$

320,000

320,000

320,000

Total Revenue @

$24.00

$ 240,000

$ 480,000

$ 720,000

24,000

$ 16.00

Sales

Pessimistic

Likely

Optimistic

Order Quantity

Purchase Cost per unit

240,000

240,000

240,000

Order Quantity Total Cost

Sales

Order Quantity

Purchase Cost per unit

$

$

$

18,000

16.00

Sales

Order Quantity

Purchase Cost per unit

15,000

15,000

15,000

Total Revenue @

$24.00

$ 240,000

$ 480,000

$ 720,000

$

Order Quantity Total Cost

10,000

20,000

30,000

24,000

24,000

24,000

$

$

$

384,000

384,000

384,000

Total Revenue @

$24.00

$ 240,000

$ 480,000

$ 720,000

28,000

16.00

Sales

Pessimistic

Likely

Optimistic

Order Quantity Total Cost

10,000

20,000

30,000

28,000

28,000

28,000

$

$

$

448,000

448,000

448,000

Total Revenue @

$24.00

$ 240,000

$ 480,000

$ 720,000

Total Revenue @

$5.00

$ 25,000

N/A

N/A

Profit

Total Revenue @

$5.00

$ 40,000

N/A

N/A

Profit

$

$

$

$

$

$

25,000

240,000

480,000

(8,000)

192,000

432,000

Total Revenue @

Profit

$5.00

$ 50,000 $ (30,000)

$ 160,000

$ 400,000

Total Revenue @

$5.00

$ 70,000

$ 20,000

N/A

Profit

Total Revenue @

$5.00

$ 90,000

$ 40,000

N/A

Profit

$

$

$

(74,000)

116,000

336,000

$ (118,000)

$

72,000

$ 272,000

Column1

Mean

Standard Error

Median

Mode

Standard Deviation

Sample Variance

Kurtosis

Skewness

Range

Minimum

Maximum

Sum

Count

Confidence Level(95.0%)

20000

5773.503

20000

#N/A

10000

1E+08

#DIV/0!

0

20000

10000

30000

60000

3

24841.38

10000

15000

18000

20000

24000

28000

30000

Column1

Mean

Standard Error

Median

Mode

Standard Deviation

Sample Variance

Kurtosis

Skewness

Range

Minimum

Maximum

Sum

Count

Confidence Level(95.0%)

20714.29

2696.685

20000

#N/A

7134.757

50904762

-0.95758

-0.13751

20000

10000

30000

145000

7

6598.55

Order Quantity

Purchase Cost per unit

$

16.00

Sales

Pessimistic

Likely

Optimistic

Order Quantity Total Cost

10,000

20,000

30,000

Total Revenue

@ $24.00 @ $5.00

Profit

1

SuperFun Toys Case Study

Team A

2

SuperFun Toys Case Study

SuperFun Toys, Inc., sells a variety of new and innovative children’s toys. Management

learned the pre-holiday season is the best time to introduce a new toy because many families use

this time to look for new ideas for December holiday gifts. When SuperFun discovers a new toy

with good market potential, it chooses an October market entry date. To get toys in its stores by

October, SuperFun places one-time orders with its manufacturers in June or July of each year.

Demand for children’s toys can be highly volatile. If a new toy catches on, a sense of

shortage in the marketplace often increases the demand to high levels and large profits can be

realized. However, new toys can also flop, leaving SuperFun stuck with high levels of inventory

that must be sold at reduced prices. The most important question the company faces is deciding

how many units of a new toy should be purchased to meet anticipated sales demand. If too few

are purchased, sales will be lost; if too many are purchased, profits will be reduced because of

low prices realized in clearance sales. SuperFun plans to introduce a new product called Weather

Teddy

This paper will use the sales forecaster’s prediction to describe a normal probability

distribution that can be used to approximate the demand distribution, sketch the distribution and

show its mean and standard deviation, compute the probability of a stock-out for the order

quantities suggested by members of the management team, compute the projected profit for the

order quantities suggested by the management team under three scenarios, and find the profit

potential the order quantity should have a 70% chance of meeting demand and only a 30%

chance of any stock- outs.

Normal Probability Distribution

3

Since SuperFun’s senior sales forecaster predicted an expected demand of 20,000 units

with a 95% probability that demand would be between 10,000 units and 30,000 units. Then

20,000 will be the mean and 5000 ((30000-20000)/2) would be the standard deviation. The Z

score would be 1.96 and as said above the probability would be .95. Where P(10000 < X
<30000) =0.95. Since the Z score is 1.96, the means the standard deviation is (3000020000)/1.96 = 5102. This would indicate a normal distribution that would be used to
approximate the demand distribution.
Sketch the Distribution
Somebody
Probability of a Stock-Out
Somebody
Projected Profit
The below table has computed the projected profit for the order quantities suggested by the
management team under three scenarios: pessimistic in which sales are 10,000 units, most likely
case in which sales are 20,000 units, and optimistic in which sales are 30,000 units.
4
Order Quantity
Purchase Cost per unit
$
15,000
16.00
Sales
Pessimistic
Likely
Optimistic
Order Quantity
Purchase Cost per unit
$
Order Quantity Total Cost
10,000
20,000
30,000
Pessimistic
Likely
Optimistic
$
Order Quantity Total Cost
10,000
20,000
30,000
Pessimistic
Likely
Optimistic
$
Profit
$ (8,000)
$ 192,000
$ 432,000
10,000
20,000
30,000
20,000 $
20,000 $
20,000 $
Total Revenue @
$24.00
$5.00
320,000 $ 240,000 $ 50,000
320,000 $ 480,000
320,000 $ 720,000
Profit
$ (30,000)
$ 160,000
$ 400,000
24,000
16.00
Pessimistic
Likely
Optimistic
$
18,000 $
18,000 $
18,000 $
Total Revenue @
$24.00
$5.00
288,000 $ 240,000 $ 40,000
288,000 $ 480,000 N/A
288,000 $ 720,000 N/A
Order Quantity Total Cost
Sales
Order Quantity
Purchase Cost per unit
$ 25,000
$ 240,000
$ 480,000
20,000
16.00
Sales
Order Quantity
Purchase Cost per unit
Profit
18,000
16.00
Sales
Order Quantity
Purchase Cost per unit
15,000 $
15,000 $
15,000 $
Total Revenue @
$24.00
$5.00
240,000 $ 240,000 $ 25,000
240,000 $ 480,000 N/A
240,000 $ 720,000 N/A
Order Quantity Total Cost
10,000
20,000
30,000
24,000 $
24,000 $
24,000 $
Total Revenue @
$24.00
$5.00
384,000 $ 240,000 $ 70,000
384,000 $ 480,000 $ 20,000
384,000 $ 720,000 N/A
Profit
$ (74,000)
$ 116,000
$ 336,000
28,000
16.00
Sales
Pessimistic
Likely
Optimistic
Order Quantity Total Cost
10,000
20,000
30,000
28,000 $
28,000 $
28,000 $
Total Revenue @
$24.00
$5.00
448,000 $ 240,000 $ 90,000
448,000 $ 480,000 $ 40,000
448,000 $ 720,000 N/A
Recommended Quantity and Profit (Mac)
Blah blah blah
Profit
$ (118,000)
$ 72,000
$ 272,000
5
Conclusion
In conclusion this paper has described a normal probability distribution that can be used to
approximate the demand distribution, sketched the distribution and show its mean and standard
deviation, computed the probability of a stock-out for the order quantities suggested by members
of the management team, computed the projected profit for the order quantities suggested by the
management team under three scenarios, and found the profit potential the order quantity should
have a 70% chance of meeting demand and only a 30% chance of any stock- outs.
6
References
Black, K. (2017). Business Statistics: For Contemporary Decision Making. (9th Edition).
Retrieved from the University of Phoenix Online eBook Collection.
Investopedia, 2018. Retrieved from https://www.investopedia.com/
...
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