Munoz Company produces commercial gardening equipment. Since production is highly automated, the company allocates its overhead costs to product lines using activity-based costing. The costs and cost drivers associated with the four overhead activity cost pools follow:

Production of 860 sets of cutting shears, one of the company’s 20 products, took 250 labor hours and 9 setups and consumed 20 percent of the product-sustaining activities.

Required

1. Had the company used labor hours as a company wide allocation base, how much overhead would it have allocated to the cutting shears?

2. How much overhead is allocated to the cutting shears using activity-based costing?

3. Compute the overhead cost per unit for cutting shears first using activity-based costing and then using direct labor hours for allocation if 860 units are produced. If direct product costs are $120 and the product is priced at 30 percent above cost for what price would the product sell under each allocation system?

Compute the overhead cost per unit for cutting shears first using activity-based costing and then using direct labor hours for allocation if 860 units are produced. If direct product costs are $120 and the product is priced at 30 percent above cost for what price would the product sell under each allocation system? (Round intermediate calculations and final answers to 2 decimal places.)

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5. Present value

To find the present value of a cash flow expected to be paid or received in the future, you will   the future value cash flow by (1 + I)NN.

What is the value today of a $12,000 cash flow expected to be received eight years from now based on an annual interest rate of 6%?

$9,411

$6,023

$11,670

$7,529

Your broker called earlier today and offered you the opportunity to invest in a security. As a friend, she suggested that you compare the current, or present value, cost of the security and the discounted value of its expected future cash flows before deciding whether or not to invest. The decision rule that should be used to decide whether or not to invest should be:

Everything else being equal, you should invest if the discounted value of the security’s expected future cash flows is greater than or equal to the current cost of the security.

Everything else being equal, you should invest if the present value of the security’s expected future cash flows is less than the current cost of the security.

Everything else being equal, you should invest if the current cost of the security is greater than the present value of the security’s expected future cash flows.

Now that you’ve thought about the decision rule that should be applied to your decision, apply it to the following security offered by your broker:

Jing Associates, LLC, a large law firm in Denver, is building a new office complex. To pay for the construction, Jing Associates is selling a security that will pay the investor the lump sum of $6,750 in five years. The current market price of the security is $5,896.

Assuming that you can earn an annual return of 3.75% on your next most attractive investment, how much is the security worth to you today?

$7,019

$5,334

$5,615

From strictly a financial perspective, should you invest in the Jing security?

Yes

No

Why or why not?

Because the cost (market value) of the security is greater than the discounted value of the security’s future cash flows.

Because the discounted value of the security’s future cash flows is greater than the cost of the security.

A power plant is planning construction of a new plant to generate electricity four years hence and must decide now between a small, medium, or large-sized plant. The exact size needed is uncertain because future demands can only be estimated. Forecasters have estimated future demands and their likelihoods as follows:

            In the following, all the future costs and earnings have been adjusted to their present worth:

1. The capacity of a small plant would limit its NPV to $60 million regardless of demand. If demand is medium, a small plant can be enlarged a moderate amount at a cost of $20 million. Its NPV would then be $110 million less the cost of $20 million for the expansion. If demand is high, a small plant can be enlarged greatly in size at a cost of $80 million. Its NPV would then be $170 million less the cost of $80 million for the expansion. On the contrary, if demand is high, a small plant can be enlarged a moderate amount to increase its NPV to $140 million less the cost of $40 million for the expansion.
2. A medium-sized plant will have an NPV of $120 million if demand is high or medium and a loss of $5 million if demand is low. If demand is high, a medium-sized plant can be enlarged at a cost of $40 million to generate an additional $80 million in earnings.
3. If a large plant is built and demand is high, the plant’s net present value (NPV) is estimated to be $180 million. If the demand is medium, however, the NPV of a large plant will drop to $100 million. If the demand is low the NPV will be loss of $200 million.

Use decision-tree analysis in MS Excel to determine the size of the power-generating plant the company should build now. (Please show the formulas in the cells)

Questions:

1. What size of the power-generating plant the company should build now?

2. Will the answer be the same if you will change the forecasters estimated demands and their likelihoods to:

Short Answer Writing Assignment All answers should be complete sentences.

In the Week 2 Lab, you found the mean and the standard deviation for the SLEEP variable for both males and females. Use those values for follow these directions to calculate the numbers again.

(From Week 2 Lab: Calculate descriptive statistics for the variable Sleep by Gender. Sort the data by gender by clicking on Data and then Sort. Copy the Sleep of the males from the data file into the Descriptive Statistics worksheet of the Week 1 Excel file. [Write down the mean and standard deviation.] These are sample data. Then, copy and paste the female data into the Descriptive Statistics workbook and do the same. Keep three decimal places.)

You will also need the number of males and the number of females in the dataset. You can actually count these in the dataset. Then use the Week 5 spreadsheet to calculate the following confidence intervals. The male confidence interval would be one calculation in the spreadsheet and the females would be a second calculation.

1. Give and interpret the 95% confidence intervals for males and a second 95% confidence interval for females on the SLEEP variable. Which is wider and why?

2. Give and interpret the 99% confidence intervals for males and a second 99% confidence interval for females on the SLEEP variable. Which is wider and why? We need to find the confidence interval for the SHOE SIZE variable. To do this, we need to find the mean and standard deviation with the Week 1 spreadsheet. Then we can the Week 5 spreadsheet to find the confidence interval. This does not need to be separated by males and females, rather one interval for the entire data set. First, find the mean and standard deviation by copying the SHOE SIZE variable and pasting it into the Week 1 spreadsheet. Write down the mean and the sample standard deviation as well as the count. Open the Week 5 spreadsheet and type in the values needed in the green cells at the top to find the confidence interval.

3. Give and interpret the 95% confidence interval for the size of students’ shoes. Change the confidence level to 99% to find the 99% confidence interval for the SHOE SIZE variable.

4. Give and interpret the 99% confidence interval for the size of students’ shoes.

5. Compare the 95% and 99% confidence intervals for the size of students’ shoes. Explain the difference between these intervals and why this difference occurs.

6. Find the mean and standard deviation of the DRIVE variable by copying that variable into the Week 1 spreadsheet. Use the Week 4 spreadsheet to determine the percentage of data points from that data set that we would expect to be less than 25. To find the actual percentage in the dataset, sort the DRIVE variable and count how many of the data points are less than 25 out of the total 35 data points. That is the actual percentage. How does this compare with your prediction? Mean: ______________ Standard deviation: ____________________ Predicted percentage: Actual percentage: Comparison ___________________________________________________ ______________________________________________________________

7. What percentage of data would you predict would be between 25 and 50 and what percentage would you predict would be more than 50 miles? Use the Week 4 spreadsheet again to find the percentage of the data set we expect to have values between 25 and 50 as well as for more than 50. Now determine the percentage of data points in the dataset that fall within each of these ranges, using same strategy as above for counting data points in the data set. How do each of these compare with your prediction and why is there a difference? Predicted percentage between 25 and 50: ______________________________ Actual percentage: Predicted percentage more than 50 miles: Actual percentage: ___________________________________________ Comparison ____________________________________________________ _______________________________________________________________ Why? __________________________________________________________ ________________________________________________________________

We need to find the confidence interval for the SLEEP variable. To do this, we need to find the mean and standard deviation with the Week 1 spreadsheet. Then we can the Week 5 spreadsheet to find the confidence interval.

First, find the mean and standard deviation by copying the SLEEP variable and pasting it into the Week 1 spreadsheet. Write down the mean and the sample standard deviation as well as the count. Open the Week 5 spreadsheet and type in the values needed in the green cells at the top. The confidence interval is shown in the yellow cells as the lower limit and the upper limit.

1. Give and interpret the 95% confidence interval for the hours of sleep a student gets.
2. Give and interpret the 99% confidence interval for the hours of sleep a student gets
3. Compare the 95% and 99% confidence intervals for the hours of sleep a student gets. Explain the difference between these intervals and why this difference occurs.

In the Week 2 Lab, you found the mean and the standard deviation for the HEIGHT variable for both males and females. Use those values for follow these directions to calculate the numbers again.

(From Week 2 Lab: Calculate descriptive statistics for the variable Height by Gender. Click on Insert and then Pivot Table. Click in the top box and select all the data (including labels) from Height through Gender. Also click on “new worksheet” and then OK. On the right of the new sheet, click on Height and Gender, making sure that Gender is in the Rows box and Height is in the Values box.   Click on the down arrow next to Height in the Values box and select Value Field Settings. In the pop up box, click Average then OK. Write these down. Then click on the down arrow next to Height in the Values box again and select Value Field Settings. In the pop up box, click on StdDev then OK. Write these values down.)

You will also need the number of males and the number of females in the dataset. You can either use the same pivot table created above by selecting Count in the Value Field Settings, or you can actually count in the dataset.

Then use the Week 5 spreadsheet to calculate the following confidence intervals. The male confidence interval would be one calculation in the spreadsheet and the females would be a second calculation.

1. Give and interpret the 95% confidence intervals for males and females on the HEIGHT variable. Which is wider and why?

2. Give and interpret the 99% confidence intervals for males and females on the HEIGHT variable. Which is wider and why?

3. Find the mean and standard deviation of the DRIVE variable by copying that variable into the Week 1 spreadsheet. Use the Week 4 spreadsheet to determine the percentage of data points from that data set that we would expect to be less than 40. To find the actual percentage in the dataset, sort the DRIVE variable and count how many of the data points are less than 40 out of the total 35 data points. That is the actual percentage. How does this compare with your prediction?

4. What percentage of data would you predict would be between 40 and 70 and what percentage would you predict would be more than 70 miles? Use the Week 4 spreadsheet again to find the percentage of the data set we expect to have values between 40 and 70 as well as for more than 70. Now determine the percentage of data points in the dataset that fall within this range, using same strategy as above for counting data points in the data set. How do each of these compare with your prediction and why is there a difference?

Please provide a step by step solution

Key the names in indexing order using the ARMA rules. In the upper right corner of each card, key the corresponding number for each name

1. James R. Larsen
2. Bob O’Donald
3. Helen Vandermallie
4. Martha Odell-Ryan
5. Sister Catherine
6. George Harris, Ph.D.
7. Mrs. Georgia Harris
8. Father Jenkins
9. Ty Chen
10. Martha Odellman
11. Allens Swap Shop
12. J. T. Larson
13. Herbert Vander Mallie
14. George Harris, M.D.
15. Mary Allen’s Beauty Shop
16. Marshall Field & Company
17. Georgia Harris
18. Allens’ Print Shop
19. Trans-Continent Truckers
20. George Harris
21. James Larson
22. Hubert Vander Mallie
23. George E. Harris
24. Cayuga Industries
25. North East Fuel Supply
26. AAA Batteries
27. CHAM Radio
28. Higgins Cleaners
29. Electronics Laboratory, General Electric Company
30. Niagara Office Supply
31. Over-30 Club
32. Prince Arthur’s Hair Styling
33. C & H Television Repair
34. First Baptist Church
35. Hotel Isabella

36.   James Danforth, Jr.
37. Burns Travel Agency
38. Strathcona County Water Department
39. Norton R. Henson
40. Sister Marie O’Doul
41. The Lone Ranger Riding Supplies
42. The Jefferson Party House
43. El Rancho Inn
44. Cecil Young-Jones
45. RCT Manufacturers
46. Administrative Management Society
47. Hotel Baker
48. Triple-Star Enterprises
49. Miss Robert’s Charm School
50. Acadia University, Wolfville, Nova Scotia
51. Bob Guerin
52. William T. Au
53. Thomas Kaplan, M.D.
54. Irene McGregor
55. Arthur P. Van der Linden
56. Ontario Municipal Board
57. John Wilkins Supply Corp.
58. Southwestern Distributors
59. Department of Employment and Immigration
60. Four Corners Answering Service
61. Reliable Answering Service
62. Montgomery Ward & Co.
63. South East Pipeline
64. Webbers’ Home for the Aged
65. People’s Republic of China
66. Prince Albert Printing Co.
67. The Mercantile Bank of Canada
68. Aero Bolt and Screw Co., Montreal
69. Strong Memorial Hospital
70. .Surv-Ur-Self Pastries, Inc

1) Donald rents out his vacation home for nine months and lives in his vacation home for the remainder of the year. His gross rental income for 2017 is $7,200. The expenses attributable to the vacation home for the entire year are as follows:

Real estate taxes $2,000

INterest on mortgage loan 4,000

Utilities 1,200

Repairs/maintenance 600

Depreciation 3,500

What amount would Donald report as net income or loss from the rental of the vacation home?

2) Wilson and Joan, both in their 30s, file a joint income tax return for 2017. Wilson's wages are $15,000 and Joan's wages are $23,000 for the year. Their total adjusted gross income is $38,000, and Joan is covered by a qualified pension plan at work but Wilson is not.

a) What is the maximum amount that Wilson and Joan may each deduct for contributions to thier individual retirement accounts?

Wilson $

Joan $

b) If Joan's wages are $82,000 for 2017, instead of $23,000, and thier adjusted gross income is $97,000, what is the maximum amount that Wilson and Joan may each deduct for contributions to thier individual retirement accounts?

Wilson $

Joan $

3) Hope srpings, a teacher, loaned Hugh Owens, a friend, $20,000 to invest in real estate. Hugh declared bankruptcy in 2017 and cannot repay the $20,000

a) What is the nature of Hope's loss? ( what does it called ?)

b) Assuming Hope has no other captial transactions, is there a limit on the amount she may deduct for 2017?

Explain

4) Dennis, the owner of Dennis Company, incurs the following expenses while away from home on a three-week business trip during 2017:

Air fare from Chicago to Boston $800

Hotel charges 2,200

Meal charges 880

Dry cleaning and laundry 100

Local transportation 55

Business entertainment 250

Business gift to Boston manager 55

in addition to the above expenses, Dennis incurred the following expenses for a weekend sightseeing trip to Washington D.C.:

Transportation to Washington DC $350

Hotel charges 225

Meal charges 105

Calcuate the amount Dennis may deduct for 2017 as travel expenses for the trip

Transformers Industry & Technology Inc. is a diversified industrial company. The Company owns businesses providing products & services to the energy, transportation, chemical, and construction sectors.

The energy segment operates as an oil and natural gas contract drilling company the United States. The energy segment acquires, explores, develops, and produces oil and natural gas properties primarily located in Oklahoma and Texas, as well as in Arkansas, Colorado, Kansas, Louisiana, Mississippi, Montana, New Mexico, North Dakota, Utah, and Wyoming. This segment generated over $10 billion of revenue in 2016.

The transportation segment is among the largest public railroad in North America. Operating on 12,000 miles of track in the western one thirds of the U.S., This segment generated over $20 billion of revenue in 2016 by hauling coal, industrial products, intermodal containers, agriculture goods, chemicals, and automotive goods.

The chemical segment sells value-added chemicals, thermoplastic polymers, and other chemical-based products worldwide. This segment develops, produces, and supplies specialty polymers for automotive and medical applications, as well as for use in industrial products and consumer electronics. This segment generated over $5 billion of revenue in 2016.

The Construction segment produces and sells specialty construction chemicals, specialty building materials, and packaging sealants and coatings. The Company operates through two segments: Specialty Construction Chemicals and Specialty Building Materials. The Specialty Construction Chemicals segment manufactures and markets products to manage performance of Portland cement, and materials based on Portland cement, such as concrete admixtures and cement additives, as well as concrete production management systems. The Specialty Building Materials segment manufactures and markets building envelope products, residential building products and specialty construction products. This segment generated over $5 billion of revenue in 2016.

During the last few years, Transformers Industry has been too constrained by the high cost of capital to make many capital investments. Recently, though, capital costs have been declining, and the company has decided to look seriously at a major expansion program that has been proposed by the marketing department. The expansion requires investment in eight projects from the four segments. Table-1 provides information about the projects.

Assume that you are an assistant to Jim Jones, the financial vice president. Your first task is to estimate Transformers cost of capital.

As a part of your analysis you have collected the following data:

The firm's tax rate is 40%.

The current price of Transformers 12% coupon, semiannual payment, non-callable bonds with 15 years remaining to maturity is $1,153.72. TPIT does not use short-term interest-bearing debt on a permanent basis. New bonds would be privately placed with no flotation cost.

The current price of the firm’s 10%, $100 par value, quarterly dividend, perpetual preferred stock is $116.95. Transformers would incur flotation costs equal to 5% of the proceeds on a new issue.

Transformers common stock is currently selling at $50 per share. Its last dividend was $3.12, and dividends are expected to grow at a constant rate of 5.8% in the foreseeable future. Transformers beta is 1.2, the yield on T-bonds is 5.6%, and the market risk premium is estimated to be 6%.

Suppose the firm has historically earned 15% on equity (ROE) and retained 35% of earnings, and investors expect this situation to continue in the future. How could you use this information to estimate the future dividend growth rate, and what growth rate would you get? Is this consistent with the 5.8% growth rate given earlier?

Transformers target capital structure is 30% long-term debt, 10% preferred stock, and 60% common equity.

Suggested questions

1) What sources of capital should be included when you estimate Transformers weighted average cost of capital (WACC)?

2) Should the component costs be figured on a before-tax or an after-tax basis?

3) Should the costs be historical (embedded) costs or new (marginal) costs? Explain?

4) Transformers preferred stock is riskier to investors than its debt, yet the preferred yield to investors is lower than the yield to maturity on the debt. Does this suggest that you have made a mistake? (Hint: Think about taxes.)

5) What is the market interest rate on Transformers debt and what is the component cost of this debt for WACC purposes?

6) What is the corporate cost of capital?

Part 2

1) Jim Jones was worried that whether the corporate cost of capital would be appropriate to evaluate the four segments’ project. His concern centered on whether the risk of the projects is reflected on the corporate cost of capital? What is the logical method of adjusting the cost of capital for risk? Is it wise to use the corporate cost of capital to evaluate the four segments’ projects?

2) Discuss the quantitative methods that are useful to evaluate the projects?

3) Discuss the strengths and weakness of each quantitative method you have selected to evaluate the projects?

4) Will all of the quantitative methods rank the projects identically? Why or why not?

5) Rank the projects on the basis of the measurements discussed above.