Variable Costing Income Statement for a Service Company
East Coast Railroad Company transports commodities among three routes (city-pairs): Atlanta/Baltimore, Baltimore/Pittsburgh, and Pittsburgh/Atlanta. Significant costs, their cost behavior, and activity rates for April are as follows:
| Cost | Amount | Cost Behavior | Activity Rate | |||
| Labor costs for loading and unloading railcars | $186,930 | Variable | $46.50 | per railcar | ||
| Fuel costs | 399,040 | Variable | 11.60 | per train-mile | ||
| Train crew labor costs | 233,920 | Variable | 6.80 | per train-mile | ||
| Switchyard labor costs | 123,414 | Variable | 30.70 | per railcar | ||
| Track and equipment depreciation | 198,100 | Fixed | ||||
| Maintenance | 132,100 | Fixed | ||||
Operating statistics from the management information system reveal the following for April:
| Atlanta/ Baltimore |
Baltimore/ Pittsburgh |
Pittsburgh/ Atlanta |
Total | |||||
| Number of train-miles | 12,080 | 9,520 | 12,800 | 34,400 | ||||
| Number of railcars | 630 | 2,120 | 1,270 | 4,020 | ||||
| Revenue per railcar | $517 | $248 | $401 | |||||
a. Prepare a contribution margin by route report for East Coast Railroad Company for the month of April. Calculate the contribution margin ratio, rounded to one decimal place.
| East Coast Railroad Company | ||||
| Contribution Margin by Route | ||||
| For the Month Ended April 30 | ||||
| Atlanta/Baltimore | Baltimore/Pittsburgh | Pittsburgh/Atlanta | Total | |
| Revenues | $ | $ | $ | $ |
| Variable costs: | ||||
| Labor costs for loading and unloading railcars | $ | $ | $ | $ |
| Fuel costs | ||||
| Train crew labor costs | ||||
| Switchyard labor costs | ||||
| Total variable costs | $ | $ | $ | $ |
| Contribution margin | $ | $ | $ | $ |
| Contribution margin ratio | % | % | % | % |
b. Evaluate the route performance of the railroad using the report in (a).
The route performs significantly worse than do the other two routes. A close examination of the operating statistics indicates that this route runs railcars, combined with fairly total mileage. This combination suggests that the railroad is running many trains on the railroad. That is, the railroad’s profitability is sensitive to the size, or length, of the train in railcar terms.
In: Accounting
The Smith family lives in Scranton, PA. Mr. Smith work in a factory producing widgets that are used and bought by automobile manufacturing. His factory job pays and annual salary of $31,000 per year, with overtime when available, he makes up to an additional $8,000.
The mother is a stay at home mother raising five children, ages of 6 months, 2 years, 3 years, 4 years, and 6 years of age.Mr. Smith was recently laid off. Because of the severance that was paid totaling $20,000 and the salary already received throughout the year, the Smith's currently do not qualify for Medical Assistance. The children have been able to receive the CHIP program.
The ABC cancer foundation has been engaging in a mass breast cancer awareness campaign indicating the need for women to get checks, risks, and benefits. As part of the project, the ABC cancer foundation has been offering free breast cancer (mammograms) for women with limited or no insurance. Mrs. Smith decides to participate in the program. As a result of the exam, a tumor is found. Labs were taken and the tumor came back malignant. XYZ Hospital is a non-profit hospital in the region. It is only hospital in the region.
closest hospital to XYZ is 50 miles away. Over the past five years, XYZ hospital has been experiencing significant declines in cash flow, layoffs, and operating deficiencies.
Days cash on hand is at 5 days. The industry average is 85 days cash on hand. The hospital is in jeopardy of going bankrupt.The Smith family presented in the emergency room with the lab results indicating a malignant tumor. XYZ hospital staff knows that if a surgical procedure was scheduled, additional staff, medical supplies, and resources would be needed.
What does the hospital administration do? In your reflection, place yourself in both the family role and also as the CFO. (Reference the Ignatian and Jesuit articles in the resource section as well as you own values and perspective on hospital survival). What implications to the community, the family, the hospital, etc.?
In: Accounting
Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below.
| ANOVA table | |||||
| Source | SS | df | MS | F | |
| Regression | 1,830.5782 | 1 | 1,830.5782 | 41.15 | |
| Residual | 1,245.4934 | 28 | 44.4819 | ||
| Total | 3,076.0716 | 29 | |||
| Regression output | |||
| Variables | Coefficients | Std. Error | t(df=28) |
| Intercept | 14.1988 | 3.137 | 2.962 |
| Distance–X | 3.9798 | 0.6204 | 6.42 |
a-1. Write out the regression equation. (Round your answers to 3 decimal places.)
a-2. Is there a direct or indirect relationship between the distance from the fire station and the amount of fire damage?
How much damage would you estimate for a fire 9 miles from the nearest fire station? (Round your answer to the nearest dollar amount.)
c-1. Determine and interpret the coefficient of determination. (Round your answer to 3 decimal places.)
c-2. Fill in the blank below. (Round your answer to one decimal place.)
____% of the variation in damage is explained by variation in distance.
d-1. Determine the correlation coefficient. (Round your answer to 3 decimal places.)
d-3. How did you determine the sign of the correlation coefficient?
e-1. State the decision rule for 0.01 significance level: H0 : ρ = 0; H1 : ρ ≠ 0. (Negative value should be indicated by a minus sign. Round your answers to 3 decimal places.)
e-2. Compute the value of the test statistic. (Round your answer to 2 decimal places.)
e-3. Is there any significant relationship between the distance from the fire station and the amount of damage? Use the 0.01 significance level.
In: Statistics and Probability
You are a real estate developer and are trying to determine the EMV of your net commission from a sales call to a potential purchaser.
Assume that your transportation cost is $1.45 per mile
Assume that the sales call is 70 miles round trip
Assume that your transportation time is 2.25 minutes per mile
Assume that the value of your time for transportation is $55.00 per hour
Assume that it will take 3 hours to meet with the potential purchaser
Assume that the value of your time for the customer meeting is $150.00 per hour
Assume that you will have a 19% chance of a successful sales call (sales call #1)
If sales call #1 is successful,
you will sell a house valued at $275,000 with likelihood = 55%
you will sell a house valued at $300,000 with likelihood = 35%
you will sell a house valued at $425,000 with likelihood = 10%
Assume that your commission will be 2.5% of the value of the house if sales call #1 is successful.
a) What is the expected cost (time and transportation) of sales call #1?
b) Without assuming that the sales call will be successful (that is, it may or may not be a success), what is the expected gross commission of sales call #1 (do not net out the expected costs)?
Suppose you have a second possible sales call (sales call #2). Assume that the expected cost remains the same and that the commission rate remains 2.5%, but that the following information is the different information for sales call #2.
Assume that you will have a 12% chance of a successful sales call (sales call #2) If sales call #2 is successful,
you will sell a house valued at $285,000 with likelihood = 45%
you will sell a house valued at $320,000 with likelihood = 25%
you will sell a house valued at $355,000 with likelihood = 30%
c) Assuming that your sales call is successful, look at the worst possible outcome for each decision and choose the decision that has the best (or least bad) of these.
In: Statistics and Probability
This file is from a statistics textbook and
provides information on over 100 recently sold homes in a town in Arizona (fictional). The variables that
are included are:
Price: Sales prices in thousands of dollars
Bedrooms: Number of bedrooms
Baths: Number of bathrooms
Size: Size of the house measured in square feet
Pool: Variable is 0 if no pool, and 1 if there is a pool
Garage: Variable is 0 if no garage, and 1 if there is a garage
Distance: This is the number of miles that the house is from city center
Township: There are five townships in the town. This identifies the township the house is in
Part 1: Identify whether each variable is qualitative or quantitative. Then identify whether each
variable is nominal, ordinal, interval, or ratio.
Part 2: Use statistical techniques to provide a summary of the homes in this town. This can include
summary statistics and/or graphs. Think about what type of information is contained in each variable
(part 1) before you select summary techniques.
Part 3: Choose two townships and compare some aspects of the homes in each township. Please
consider both qualitative and quantitative characteristics. If a variable is quantitative please consider
measures of center and measures of dispersion when possible.
| Price | Bedrooms | Size | Pool | Distance | Twnship | Garage | Baths |
| 263.1 | 4 | 2300 | 1 | 17 | 5 | 1 | 2 |
| 182.4 | 4 | 2100 | 0 | 19 | 4 | 0 | 2 |
| 242.1 | 3 | 2300 | 0 | 12 | 3 | 0 | 2 |
| 213.6 | 2 | 2200 | 0 | 16 | 2 | 0 | 2.5 |
| 139.9 | 2 | 2100 | 0 | 28 | 1 | 0 | 1.5 |
| 245.4 | 2 | 2100 | 1 | 12 | 1 | 1 | 2 |
| 327.2 | 6 | 2500 | 0 | 15 | 3 | 1 | 2 |
| 271.8 | 2 | 2100 | 0 | 9 | 2 | 1 | 2.5 |
| 221.1 | 3 | 2300 | 1 | 18 | 1 | 0 | 1.5 |
| 266.6 | 4 | 2400 | 0 | 13 | 4 | 1 | 2 |
| 292.4 | 4 | 2100 | 0 | 14 | 3 | 1 | 2 |
In: Statistics and Probability
Liam is a 17-year-old male who is being seen by his family physician for his annual physical examination. Liam’s sexual maturation rating is estimated to be 3. He weighs 114 lbs and stands 5’6” tall.
When he was 16 y.o., his height was 5’5” and weight was 106 lbs.
At 15 y.o., Liam was 5’3” tall and weighed 98lbs.
During the visit, Liam reports that he has been experimenting with a vegan diet since his visit last year. He explains that he thinks it is a healthier way to eat and states that he avoids milk, beef, and pork eats poultry or fish once every two weeks and eats cheese 3-4x/wk. Breakfast is usually cold cereal with almond milk because he heard that was a healthy milk alternative. He likes pasta, pizza, and salad, which he eats almost every day.
For exercise, he runs 3 miles 2x/wk, plays basketball with friends after school 3x/wk for an hour, and lifts weights in his garage for 45 min 5x/wk.
He says he would like to gain muscle and grow taller.
3. What clarifying questions would you like to ask Liam about his current behaviors? List 3.
4. If there is protein a concern in Liam’s diet, why? Estimate his RDA and use evidence to support your position.
5. Given Liam’s diet and exercise patterns, which dietary components may he be deficient in? For each dietary component, list possible food sources that are appropriate for his current eating pattern.
6. There are both health benefits and costs of eating mostly plants. How might his current way of eating affect Liam’s growth and maturation?
7. Is it necessary to assess Liam for the presence of an eating disorder? Provide support for your answer.
In: Nursing
Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below
| ANOVA table | ||||
| Source | SS | df | MS | F |
| Regression | 1830.5782 | 1 | 1830.5782 | 41.15 |
| Residual | 1245.4934 | 28 | 44.4819 | |
| Total | 3076.0716 | 29 | ||
| Regression output | ||||
| Variables | Coefficients | Std. Error | t(df=28) | |
| Intercept | 14.1988 | 3.137 | 2.962 | |
| Distance–X | 3.97985 | 8.842 | 6.411 | |
-1. Write out the regression equation. (Round your answers to 3 decimal places.) a-2. Is there a direct or indirect relationship between the distance from the fire station and the amount of fire damage? How much damage would you estimate for a fire 9 miles from the nearest fire station? (Round your answer to the nearest dollar amount.) c-1. Determine and interpret the coefficient of determination. (Round your answer to 3 decimal places.) c-2. Fill in the blank below. (Round your answer to one decimal place.) d-1. Determine the correlation coefficient. (Round your answer to 3 decimal places.) d-2. Choose the right option. d-3. How did you determine the sign of the correlation coefficient? e-1. State the decision rule for 0.01 significance level: H0 : ρ = 0; H1 : ρ ≠ 0. (Negative value should be indicated by a minus sign. Round your answers to 3 decimal places.) e-2. Compute the value of the test statistic. (Round your answer to 2 decimal places.) e-3. Is there any significant relationship between the distance from the fire station and the amount of damage? Use the 0.01 significance level. rev: 10_12_2017_QC_CS-102203
In: Statistics and Probability
Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below.
| ANOVA table | ||||
| Source | SS | df | MS | F |
| Regression | 1875.5782 | 1 | 1875.5782 | 42.33 |
| Residual | 1240.4934 | 28 | 44.3033 | |
| Total | 3116.0716 | 29 | ||
| Regression output | ||||
| Variables | Coefficients | Std. Error | t(df=28) | |
| Intercept | 12.59075 | 3.1151 | 3.547 | |
| Distance–X | 2.62225 | 7.347 | 6.509 | |
Write out the regression equation. (Round your answers to 3 decimal places.)
a-2. Is there a direct or indirect relationship between the distance from the fire station and the amount of fire damage?
How much damage would you estimate for a fire 6 miles from the nearest fire station? (Round your answer to the nearest dollar amount.)
c-1. Determine the coefficient of determination. (Round your answer to 3 decimal places.)
c-2. Fill in the blank below. (Round your answer to one decimal place.)
d-1. Determine the correlation coefficient. (Round your answer to 3 decimal places.)
d-2. Choose the right option.
d-3. How did you determine the sign of the correlation coefficient?
e-1. State the decision rule for 0.01 significance level: H0 : ρ = 0; H1 : ρ ≠ 0. (Negative value should be indicated by a minus sign. Round your answers to 3 decimal places.)
e-2. Compute the value of the test statistic. (Round your answer to 2 decimal places.)
e-3. Is there any significant relationship between the distance from the fire station and the amount of damage? Use the 0.01 significance level.
In: Statistics and Probability
On Friday afternoon you received a call from a gentleman who identified himself as the chief executive officer of a firm in a small city about 100 miles from your headquarters. He wanted to charter an aircraft to make a trip to a small U.S. border town. He assured you that you would not be required to fly over the border into a foreign country or deal with customs agents. The trip would depart tomorrow (Saturday) evening, make a two-hour stop at the town’s airport, and return sometime after midnight Sunday morning.
The caller cautioned you about the confidentiality of the trip and requested that your two “most closed-mouthed” pilots fly the charter. In reply to some serious and repeated questions concerning the mission and legality of the trip and/or cargo, the caller assured you that the trip was for legal business purposes, and no contraband would be involved. He alluded to “a highly sensitive business matter” that would have an enormous effect on his firm if “the parties can agree.”
The aircraft you would have available to send is in good condition and its maintenance schedule is up-to-date; thus the trip would not endanger the readiness of the aircraft for its normal schedule the following Sunday. The prospective customer has offered you a fee that would net your firm $5,000 profit above the direct costs. The fee is somewhat large, considering the length of the trip, but the caller offered it, and you did not object.
You couldn’t find information about the firm online. Because it is late in the day on a Friday, you aren’t able to research the firm any further.
Your director of marketing is urging you to take the charter because of the potential profit and future business this firm might provide. “I’ve heard of the company. They’re in air conditioning or something like that. I’ve also heard they’re either trying to acquire another company, or they’re about to be acquired. This might be the final closing of the deal.”
1. Take the charter trip.
2. Do not take the charter trip.
In: Operations Management
A realtor studies the relationship between the size of a house (in square feet) and the property taxes (in $) owed by the owner. The table below shows a portion of the data for 20 homes in a suburb 60 miles outside of New York City.
|
Property Taxes |
Size |
|
21872 |
2434 |
|
17403 |
2423 |
|
18286 |
1875 |
|
15608 |
1043 |
|
43950 |
5637 |
|
33649 |
2524 |
|
15224 |
2214 |
|
16748 |
1926 |
|
18248 |
2006 |
|
16722 |
1339 |
|
15144 |
1379 |
|
36037 |
3043 |
|
31004 |
2866 |
|
42122 |
3304 |
|
14368 |
1504 |
|
38994 |
4073 |
|
25312 |
4100 |
|
22972 |
2457 |
|
16188 |
3510 |
|
29203 |
2805 |
a-1. Calculate the sample correlation coefficient rxy. (Round intermediate calculations to at least 4 decimal places and final answers to 4 decimal places.)
a-2. Interpret rxy.
a. The correlation coefficient indicates a positive linear relationship.
b. The correlation coefficient indicates a negative linear relationship.
c. The correlation coefficient indicates no linear relationship.
b. Specify the competing hypotheses in order to determine whether the population correlation coefficient between the size of a house and property taxes differs from zero.
a. H0: ρxy = 0; HA: ρxy ≠ 0
b. H0: ρxy ≥ 0; HA: ρxy < 0
c. H0: ρxy ≤ 0; HA: ρxy > 0
c-1. Calculate the value of the test statistic.
c-2. Find the p-value.
a. p-value < 0.01
b. p-value 0.10
c. 0.05 p-value < 0.10
d. 0.02 p-value < 0.05
e. 0.01 p-value < 0.02
d. At the 1% significance level, what is the conclusion to the test?
a. Reject H0; we can state size and property taxes are correlated.
b. Reject H0; we cannot state size and property taxes are correlated.
c. Do not reject H0; we can state size and property taxes are correlated.
d. Do not reject H0; we cannot state size and property taxes are correlated.
In: Statistics and Probability