CASE STUDY
ANNUAL WORTH ANALYSIS—THEN AND NOW
Background and Information
Harry, owner of an automobile battery distributorship in Atlanta, Georgia, performed an economic analysis 3 years ago when he decided to place surge protectors in-line for all his major pieces of testing equipment. The estimates used and the annual worth analysis at MARR = 15% are summarized below. Two different manufacturers’ protectors were compared.
|
PowrUp |
Lloyd’s |
|
|
Cost and installation, $ |
−26,000 |
−36,000 |
|
Annual maintenance cost, $ per year |
−800 |
−300 |
|
Salvage value, $ |
2,000 |
3,000 |
|
Equipment repair savings, $ |
25,000 |
35,000 |
|
Useful life, years |
6 |
10 |
The spreadsheet in below sheet is the one Harry used to make the decision. Lloyd’s was the clear choice due to its substantially larger AW value. The Lloyd’s protectors were installed.
| MARR | 15% | |||||
| PoweUp | Lloyd's | |||||
| Investment | Annual | Repair | Investment | Annual | Repair | |
| Years | and salvage | maintenance | savings | and salvage | maintenance | savings |
| 0 | -$26,000 | $0 | $0 | -$36,000 | $0 | $0 |
| 1 | $0 | -$800 | $25,000 | $0 | -$300 | $35,000 |
| 2 | $0 | -$800 | $25,000 | $0 | -$300 | $35,000 |
| 3 | $0 | -$800 | $25,000 | $0 | -$300 | $35,000 |
| 4 | $0 | -$800 | $25,000 | $0 | -$300 | $35,000 |
| 5 | $0 | -$800 | $25,000 | $0 | -$300 | $35,000 |
| 6 | $0 | -$800 | $25,000 | $0 | -$300 | $35,000 |
| 7 | $2,000 | -$800 | $25,000 | $0 | -$300 | $35,000 |
| 8 | $0 | -$300 | $35,000 | |||
| 9 | $0 | -$300 | $35,000 | |||
| 10 | $3,000 | -$300 | $35,000 | |||
| AW element | -$6,068 | -$800 | $25,000 | -$7,025 | -$300 | $35,000 |
| Total AW | $18,131.35 | $27,674.68 |
During a quick review this last year (year 3 of operation), it was obvious that the maintenance costs and repair savings have not followed (and will not follow) the estimates made 3 years ago. In fact, the maintenance contract cost (which includes quarterly inspection) is going from $300 to $1200 per year next year and will then increase 11% per year for the next 10 years. Also, the repair savings for the last 3 years were $32,901, $24,869, and $35,255, as best as Harry can determine. He believes savings will decrease by $2,577 per year hereafter. Finally, these 3-year-old protectors are worth nothing on the market now, so the salvage in 7 years is zero, not $3000.
Case Study Exercises
In: Accounting
The Robinson Corporation has $44 million of bonds outstanding that were issued at a coupon rate of 12.650 percent seven years ago. Interest rates have fallen to 11.750 percent. Mr. Brooks, the Vice-President of Finance, does not expect rates to fall any further. The bonds have 17 years left to maturity, and Mr. Brooks would like to refund the bonds with a new issue of equal amount also having 17 years to maturity. The Robinson Corporation has a tax rate of 30 percent. The underwriting cost on the old issue was 4.40 percent of the total bond value. The underwriting cost on the new issue will be 2.70 percent of the total bond value. The original bond indenture contained a five-year protection against a call, with a 6 percent call premium starting in the sixth year and scheduled to decline by one-half percent each year thereafter. (Consider the bond to be seven years old for purposes of computing the premium.) Use Appendix D for an approximate answer but calculate your final answer using the formula and financial calculator methods. Assume the discount rate is equal to the aftertax cost of new debt rounded up to the nearest whole percent (e.g. 4.06 percent should be rounded up to 5 percent).
a. Compute the discount rate. (Do not round intermediate calculations. Input your answer as a percent rounded up to the nearest whole percent.)
In: Finance
Carter Company manufactures two products, Deluxe and Regular, and uses a traditional two-stage cost allocation system. The first stage assigns all factory overhead costs to two production departments, A and B, based on machine hours. The second stage uses direct labor hours to allocate overhead to individual products.
For the current year, the firm budgeted $1,350,000 total factory overhead cost. The $1,350,000 was for the planned levels of machine and direct labor hours shown in the following table.
| Production Department A | Production Department B | |||||
| Machine hours | 5,400 | 21,600 | ||||
| Direct labor hours | 27,000 | 13,500 | ||||
The following information relates to the firm’s operations for the month of January:
| Deluxe | Regular | |||||
| Units produced and sold | 270 | 1,080 | ||||
| Unit cost of direct materials | $ | 135 | $ | 67.50 | ||
| Hourly direct labor wage rate | $ | 25 | $ | 27 | ||
| Direct labor hours in Department A per unit | 2 | 2 | ||||
| Direct labor hours in Department B per unit | 1 | 1 | ||||
Carter Company is considering implementing an activity-based costing system. Its management accountant has collected the following information for activity cost analysis for the current year:
| Budgeted | Budgeted | Driver Consumption | |||||||||||||
| Activity | Overhead | Cost Driver | Quantity | Deluxe | Regular | ||||||||||
| Material movement | $ | 9,450 | Number of production runs | 403.00 | 20.00 | 27 | |||||||||
| Machine setups | 540,000 | Number of setups | 675 | 34.00 | 68.00 | ||||||||||
| Inspections | 793,800 | Number of units | 26,460 | 270 | 1,080 | ||||||||||
| Shipment | 6,750 | Number of shipments | 338.00 | 68.00 | 135 | ||||||||||
| $ | 1,350,000 | ||||||||||||||
Required:
1. Calculate the unit cost for each of the two products under the existing volume-based costing system. (Round "Regular unit cost" to 2 decimal places.)
2. Calculate the overhead per unit of the cost driver under the proposed ABC system.
3. Calculate the unit cost for each of the two products if the proposed ABC system is adopted. (Round your intermediate calculations to 1 decimal place and final answers to 2 decimal places.)
In: Accounting
Assume that the price of Socates Motors stock will either rise to $50 or fall to $35 in one month and that the risk free rate for one month is 1.5%. How much is an option with a strike price of $40 worth if the current stock price if the current stock price is $45 instead of $40?
In: Finance
A researcher wanted to learn whether the urge to smoke cigarettes was associated with the number of times a person exercised in the last week. So the researcher gathered 10 who smoke for the study. Participants were asked to rate their urge to smoke on a scale of 0 (no urge) to 10 (extreme urge), and to give the number of times each had worked out in the last week. Using the data below, an alpha of .05 (two-tailed), use a Pearson correlation to determine the outcome.
n the box below, provide the following information:
Null Hypothesis in sentence form (1 point):
Alternative Hypothesis in sentence form (1
point):
Critical Value(s) (2 points):
Calculations (4 points): Note: the more detail you provide, the more partial credit that I can give you if you make a mistake.
Outcome (determination of significance or not, and what this reflects in everyday language, 2 points)
|
Participant |
Smoking Urge |
Workouts |
|
1 |
6 |
2 |
|
2 |
7 |
1 |
|
3 |
3 |
3 |
|
4 |
3 |
5 |
|
5 |
5 |
1 |
|
6 |
3 |
2 |
|
7 |
5 |
4 |
|
8 |
6 |
0 |
|
9 |
4 |
2 |
|
10 |
3 |
3 |
In: Statistics and Probability
A company wants to study the relationship between an employee's length of employment (x) and their number of workdays absent (y). The company collected the following information on a random sample of seven employees.
|
# of days absent(x) |
2 |
3 |
3 |
5 |
7 |
7 |
8 |
|
# of years of employment (y) |
5 |
6 |
9 |
4 |
2 |
2 |
0 |
a. Calculate the correlation coefficient r between y and x and determine if the relationship is positive or negative.
b. Find the equation of the least squares regression line.
c. Predict the number of workdays absent for an employee who has been employed for 10 years.
In: Statistics and Probability
Need Linear Regression Analysis done for the following data:
|
Day |
BP Diastolic |
Ate Healthy and Exercised |
|
1 |
85 |
N |
|
2 |
109 |
N |
|
3 |
96 |
N |
|
4 |
92 |
N |
|
5 |
99 |
N |
|
6 |
98 |
N |
|
7 |
102 |
Y |
|
8 |
93 |
N |
|
9 |
90 |
Y |
|
10 |
84 |
N |
|
11 |
90 |
N |
|
12 |
86 |
N |
|
13 |
81 |
N |
|
14 |
77 |
Y |
|
15 |
90 |
Y |
|
16 |
86 |
Y |
|
17 |
83 |
N |
|
18 |
80 |
Y |
|
19 |
78 |
N |
|
20 |
74 |
Y |
|
21 |
72 |
Y |
|
22 |
79 |
Y |
|
23 |
84 |
Y |
|
24 |
91 |
Y |
|
25 |
85 |
Y |
|
26 |
77 |
Y |
|
27 |
78 |
Y |
|
28 |
81 |
N |
|
29 |
88 |
Y |
|
30 |
85 |
Y |
|
31 |
77 |
Y |
|
32 |
74 |
Y |
|
33 |
72 |
Y |
|
34 |
77 |
N |
|
35 |
80 |
Y |
|
36 |
81 |
Y |
|
37 |
76 |
Y |
|
38 |
78 |
Y |
|
39 |
72 |
Y |
|
40 |
73 |
Y |
|
41 |
72 |
Y |
|
42 |
79 |
Y |
|
43 |
80 |
Y |
|
44 |
84 |
Y |
|
45 |
81 |
Y |
|
46 |
78 |
Y |
|
47 |
71 |
Y |
|
48 |
73 |
Y |
|
49 |
76 |
Y |
|
50 |
75 |
Y |
|
51 |
76 |
N |
|
52 |
81 |
Y |
|
53 |
78 |
N |
|
54 |
75 |
Y |
|
55 |
77 |
Y |
|
56 |
76 |
Y |
In: Statistics and Probability
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of
3939
inches. Is the result close to the actual weight of
126126
pounds? Use a significance level of 0.05.
|
Chest size (inches) |
44 |
41 |
41 |
55 |
51 |
42 |
|
|---|---|---|---|---|---|---|---|
|
Weight (pounds) |
213 |
206 |
176 |
309 |
300 |
178 |
|
n |
alphaαequals=0.05 |
alphaαequals=0.01 |
NOTE: To test
H0: rhoρequals=0 againstH1: rhoρnot equals≠0, rejectH0 if the absolute value of r is greater than the critical value in the table. |
|---|---|---|---|
|
4 |
0.950 |
0.990 |
|
|
5 |
0.878 |
0.959 |
|
|
6 |
0.811 |
0.917 |
|
|
7 |
0.754 |
0.875 |
|
|
8 |
0.707 |
0.834 |
|
|
9 |
0.666 |
0.798 |
|
|
10 |
0.632 |
0.765 |
|
|
11 |
0.602 |
0.735 |
|
|
12 |
0.576 |
0.708 |
|
|
13 |
0.553 |
0.684 |
|
|
14 |
0.532 |
0.661 |
|
|
15 |
0.514 |
0.641 |
|
|
16 |
0.497 |
0.623 |
|
|
17 |
0.482 |
0.606 |
|
|
18 |
0.468 |
0.590 |
|
|
19 |
0.456 |
0.575 |
|
|
20 |
0.444 |
0.561 |
|
|
25 |
0.396 |
0.505 |
|
|
30 |
0.361 |
0.463 |
|
|
35 |
0.335 |
0.430 |
|
|
40 |
0.312 |
0.402 |
|
|
45 |
0.294 |
0.378 |
|
|
50 |
0.279 |
0.361 |
|
|
60 |
0.254 |
0.330 |
|
|
70 |
0.236 |
0.305 |
|
|
80 |
0.220 |
0.286 |
|
|
90 |
0.207 |
0.269 |
|
|
100 |
0.196 |
0.256 |
|
|
n |
alphaαequals=0.05 |
alphaαequals=0.01 |
PrintDone
What is the regression equation?
In: Math
In: Finance
Consider the following hypothesis test. H0: μ ≤ 50 Ha: μ > 50
A sample of 60 is used and the population standard deviation is 8. Use the critical value approach to state your conclusion for each of the following sample results. Use α = 0.05. (Round your answers to two decimal places.)
(a) x = 52.3
Find the value of the test statistic. =
State the critical values for the rejection rule. (If the test is one-tailed, enter NONE for the unused tail.)
test statistic ≤ =
test statistic ≥ =
State your conclusion.
a. Do not reject H0. There is sufficient evidence to conclude that μ > 50.
b. Reject H0. There is sufficient evidence to conclude that μ > 50.
c. Reject H0. There is insufficient evidence to conclude that μ > 50.
d. Do not reject H0. There is insufficient evidence to conclude that μ > 50.
(b) x = 51
Find the value of the test statistic. =
State the critical values for the rejection rule. (If the test is one-tailed, enter NONE for the unused tail.)
test statistic ≤ =
test statistic ≥ =
State your conclusion.
a. Do not reject H0. There is sufficient evidence to conclude that μ > 50.
b. Reject H0. There is sufficient evidence to conclude that μ > 50.
c. Reject H0. There is insufficient evidence to conclude that μ > 50.
d. Do not reject H0. There is insufficient evidence to conclude that μ > 50.
(c) x = 51.8
Find the value of the test statistic. =
State the critical values for the rejection rule. (If the test is one-tailed, enter NONE for the unused tail.)
test statistic ≤ =
test statistic ≥ =
State your conclusion.
a. Do not reject H0. There is sufficient evidence to conclude that μ > 50.
b.Reject H0. There is sufficient evidence to conclude that μ > 50.
c.Reject H0. There is insufficient evidence to conclude that μ > 50.
d. Do not reject H0. There is insufficient evidence to conclude that μ > 50.
In: Statistics and Probability