Bardi Trucking Co., located in Cleveland, Ohio, makes deliveries in the Great Lakes region, the Southeast, and the Northeast. Jim Bardi, the president, is studying the relationship between the distance a shipment must travel and the length of time, in days, it takes the shipment to arrive at its destination. To investigate, Mr. Bardi selected a random sample of 20 shipments made last month. Shipping distance is the independent variable and shipping time is the dependent variable. The results are as follows:

Click here for the Excel Data File

1. Draw a scatter diagram. Based on these data, does it appear that there is a relationship between how many miles a shipment has to go and the time it takes to arrive at its destination?

1. On the graph below, use the point tool to plot the point corresponding to the first Distance and its Shipping Time (Distance 1).

2. Repeat the process for the remainder of the sample (Distance 2, Distance 3, … ).

3. To enter exact coordinates, double-click on the point and enter the exact coordinates of x and y.

4. b-1. Fill in the blanks. (Round your answers to 3 decimal places. Negative values should be indicated by minus sign.)

1. b-2. State the decision rule for 0.10 significance level: H₀: ρ ≤ 0; H₁: ρ > 0. (Round your answer to 3 decimal places.)

2. b-3. Compute the value of the test statistic. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.)

3. b-4. Can we conclude that there is a positive correlation between distance and time? Use the 0.10 significance level.

4. c-1. Determine the coefficient of determination. (Round your answer to 3 decimal places.)

5. c-2. Fill in the blank below. (Round your answer to 1 decimal place.)

________% of the variation in shipping time is explained by shipping distance.

4. Determine the standard error of estimate. (Round your answer to 3 decimal places.)

5. Would you recommend using the regression equation to predict shipping time?

• Yes

• No

Your company has sent you on business to the Los Angeles (LA) metropolitan area. Upon your arrival at LAX, you make your way to the Klunker Car Rental counter. As usual, the line at the counter is long, so you enter and begin your wait. While waiting you notice that Klunker is offering a special deal on gas. They are selling gas for $1.579 per gallon. However, you must purchase a full tank when you rent the car. Klunker also says that the average price per gallon of gas in the LA area is $1.60. You are uncertain of several necessary pieces of information to determine whether you should take advantage of this deal. These are: · the total miles you will drive on the trip; · rental car gas mileage; · how much gas the rental car's tank holds; · the true cost of gas in the LA area. First, you expect to drive between 150 and 250 miles on this trip. You believe there is an equal chance that you will drive either of these extreme amounts. However, you may have to make a side trip to Edwards AFB that will increase the total miles to 500. You believe there is a 1 in 5 chance that this will happen. Normally, Klunker rents you a mid-size car. You believe most cars in this class have either a 15 gallon gas tank with 60% confidence or a 18 gallon gas tank with 40% confidence. You've heard that cars in this class get as much as 25 mpg on the highway but may get as little as 18 mpg city driving. You decide there is an 70% chance most of your driving will be on the freeways and the rest in the city. Finally, you don't believe Klunker's posted average price of $1.60 per gallon in the LA area. You guess that there is 40% chance that the gas will be $1.259, 20% chance it will be $1.479 and a 40% chance it will be $1.659. Assume you must decide whether to pre-purchase the tank of gas prior to talking to a Klunker clerk.

a. Draw the decision tree for this problem using Decision Tree in Excel.

b. What is the optimal decision?

c. Now suppose you can delay your decision until you speak to a clerk and find out exactly how much gas your rental car holds. The clerk says the car you will rent holds 18 gallons of gas. What is your optimal decision now? What is the value of this additional information? *Please show formulas in excel*

1.

(CO7) A car company claims that the mean gas mileage for its luxury sedan is at least 24 miles per gallon. A random sample of 7 cars has a mean gas mileage of 23 miles per gallon and a standard deviation of 1.2 miles per gallon. At α=0.05, can you support the company’s claim?

Bardi Trucking Co., located in Cleveland, Ohio, makes deliveries in the Great Lakes region, the Southeast, and the Northeast. Jim Bardi, the president, is studying the relationship between the distance a shipment must travel and the length of time, in days, it takes the shipment to arrive at its destination. To investigate, Mr. Bardi selected a random sample of 20 shipments made last month. Shipping distance is the independent variable and shipping time is the dependent variable. The results are as follows:

Click here for the Excel Data File

1. Draw a scatter diagram. Based on these data, does it appear that there is a relationship between how many miles a shipment has to go and the time it takes to arrive at its destination?

1. On the graph below, use the point tool to plot the point corresponding to the first Distance and its Shipping Time (Distance 1).

2. Repeat the process for the remainder of the sample (Distance 2, Distance 3, … ).

3. To enter exact coordinates, double-click on the point and enter the exact coordinates of x and y.

1. b-1. Fill in the blanks. (Round your answers to 3 decimal places. Negative values should be indicated by minus sign.)

1. b-2. State the decision rule for 0.02 significance level: H₀: ρ ≤ 0; H₁: ρ > 0. (Round your answer to 3 decimal places.)

1. b-3. Compute the value of the test statistic. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.)

1. b-4. Can we conclude that there is a positive correlation between distance and time? Use the 0.02 significance level.

1. c-1. Determine the coefficient of determination. (Round your answer to 3 decimal places.)

1. c-2. Fill in the blank below. (Round your answer to 1 decimal place.)

4. Determine the standard error of estimate. (Round your answer to 3 decimal places.)

5. Would you recommend using the regression equation to predict shipping time?

• Yes

• No

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:

Operating statistics from the management information system reveal the following for April:

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. If required, use the minus sign to indicate a negative contribution margin.

Feedback

a. Calculate:
Revenues = revenue per railcar x number of railcars
Variable costs:
Labor costs for loading = $46 x number of railcars
Fuel costs = $12.40 x number of train-miles
Train crew labor costs = $7.20 x number of train-miles
Switchyard labor = $31 x number of railcars
Then prepare contribution margin analysis as:
Revenues - Variable costs = Contribution Margin
To calculate the contribution margin ratio, divide the contribution margin by revenues.

Learning Objective 4 and Learning Objective 6.

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.

Given the following information, prepare a Schedule C using 2019 rates.

Denise operates her business under the name "Design by Denise." Her office is located at 2359 Dawnridge Drive, Houston, Texas 77025. The federal EIN for her business is 51- 4867579 and the principal business code is 541400. Denise, who materially participates in her business, has operated it profitably for 3 of the last 4 years and is fully "at risk" with respect to her investment. She also has filed all required Forms 1099.

In accounting for her business, Denise uses the cash method. For 2019, her records show the following income and expenses. She participated in James’s health insurance plan and did not have to pay any premiums.

Gross receipts (not reported on Form 1099) . . . . . . . . . . . . . . . . . . . . . . $90,000

Gross receipts (reported on Form 1099; payer was Bernice Ng’s Furnishings, EIN 68-8752318, nonemployee compensation) . . . . 25,000 Expenses:

Advertising . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,000

Insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,000

Legal services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,500

Office expense . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,300

Equipment and machinery rent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,800

Office rent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20,000

Supplies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7,000

Taxes and licenses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,500

Utilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,400

Subscriptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 500

In connection with her business, Denise often travels from her business location to the homes and offices of her clients, where she provides advice and expertise on interior design. During 2019, her written auto log shows that she drove her vehicle (a 2018 Mitsubishi Mirage that she purchased and put in service on May 13, 2017) 22,400 miles for business purposes, 3,800 miles for commuting, and 1,800 miles for personal purposes. Denise did not keep track of all her specific expenditures for the car and she wishes to deduct her auto expenses using the standard mileage rate for 2019. She has written evidence to support her mileage. The business car was available for use during off-duty hours, but she and her spouse also have another vehicle available for personal use.

Also in connection with her business, Denise purchased a Mac computer and HP laser color printer. The computer was purchased for $2,200 on November 10, 2019. The printer was purchased for $5,800 on September 30, 2019. Denise used both the computer and printer for business purposes at her office 85 percent of the time, and personal purposes 15 percent of the time, for which she has written evidence. Denise would like to deduct the maximum allowable amount on each of these assets.

An American consumer organization is currently examining the relationship among several variables including gasoline mileage as measured by miles per gallon; the horsepower of the car’s engine and the weight of the car (in pounds). A sample of 50 recent car models was selected and the results recorded. (provided in auto.xlxs) (a) Using the sample data attached, calculate the sample mean and standard deviation for the variables: - 1. Miles per gallon (MPG) 2. Horsepower 3. Weight (in pounds) (b) Is there any evidence of skewness in the data sets? Which data set displays greatest skewness? (c) Using the sample data on MPG, calculate the sample proportion of vehicles whose fuel economy exceeds 37 mpg and its corresponding standard deviation. (d) Indicate all possible relationship between the variables and comment on it. (You may use scatter diagram or Karl Pearson’s correlation coefficient) (e) Using the complete data set and using simple ordinary least squares regression formulae develop two models to explain the behavior of gasoline mileage (Miles per gallon) as a function of their- (i) Horsepower (ii) Weight f. Which model best describes the behavior of gasoline mileage? Explain your reasons here.

MPG   Horsepower   Weight
43.1   48   1985
19.9   110   3365
19.2   105   3535
17.7   165   3445
18.1   139   3205
20.3   103   2830
21.5   115   3245
16.9   155   4360
15.5   142   4054
18.5   150   3940
27.2   71   3190
41.5   76   2144
46.6   65   2110
23.7   100   2420
27.2   84   2490
39.1   58   1755
28   88   2605
24   92   2865
20.2   139   3570
20.5   95   3155
28   90   2678
34.7   63   2215
36.1   66   1800
35.7   80   1915
20.2   85   2965
23.9   90   3420
29.9   65   2380
30.4   67   3250
36   74   1980
22.6   110   2800
36.4   67   2950
27.5   95   2560
33.7   75   2210
44.6   67   1850
32.9   100   2615
38   67   1965
24.2   120   2930
38.1   60   1968
39.4   70   2070
25.4   116   2900
31.3   75   2542
34.1   68   1985
34   88   2395
31   82   2720
27.4   80   2670
22.3   88   2890
28   79   2625
17.6   85   3465
34.4   65   3465
20.6   105   3380

Bardi Trucking Co., located in Cleveland, Ohio, makes deliveries in the Great Lakes region, the Southeast, and the Northeast. Jim Bardi, the president, is studying the relationship between the distance a shipment must travel and the length of time, in days, it takes the shipment to arrive at its destination. To investigate, Mr. Bardi selected a random sample of 20 shipments made last month. Shipping distance is the independent variable and shipping time is the dependent variable. The results are as follows:

1. Draw a scatter diagram. Based on these data, does it appear that there is a relationship between how many miles a shipment has to go and the time it takes to arrive at its destination?

1. On the graph below, use the point tool to plot the point corresponding to the first Distance and its Shipping Time (Distance 1).

2. Repeat the process for the remainder of the sample (Distance 2, Distance 3, … ).

3. To enter exact coordinates, double-click on the point and enter the exact coordinates of x and y.

4. b-1. Fill in the blanks. (Round your answers to 3 decimal places. Negative values should be indicated by minus sign.)

1. b-2. State the decision rule for 0.02 significance level: H₀: ρ ≤ 0; H₁: ρ > 0. (Round your answer to 3 decimal places.)

2. b-3. Compute the value of the test statistic. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.

3. b-4. Can we conclude that there is a positive correlation between distance and time? Use the 0.02 significance level.

4. c-1. Determine the coefficient of determination. (Round your answer to 3 decimal places.)

5. c-2. Fill in the blank below. (Round your answer to 1 decimal place.)

6. Determine the standard error of estimate. (Round your answer to 3 decimal places.)

7. Would you recommend using the regression equation to predict shipping time?

• Yes

• No

17. A tire manufacturer claims that the average life of a certain grade of tire is 50,000 miles or more when used under normal driving conditions. A random sample of 20 tires is selected and tested and the sample mean is 49,650 miles. Assume the population of the lives is to be normal with standard deviation of 5,000 miles. At the 5% significance level, the manufacturer’s claim is tested. What is the decision rule in this test?

A. Reject H₀ if Z_STAT > +1.96; otherwise, do not reject H₀.

B. Reject H₀ if Z_STAT < –1.645; otherwise, do not reject H₀.

C. Reject H₀ if t_STAT > –1.7291; otherwise, do not reject H₀.

D. Reject H₀ if t_STAT < –2.0930 or t_STAT > +2.0930; otherwise, do not reject H₀.

18. The manager of a gasoline supply corporation wants to estimate the actual amount of gasoline contained in standard 42-gallon barrels purchased from a nationally known manufacturer. The manufacturer’s specifications state that the amount of gasoline is normally distributed with a standard deviation of 0.65 gallon. A random sample of 25 barrels is selected, and the sample mean amount of gasoline per 42-gallon barrel is 42.15 gallons. Construct a 90% confidence interval estimate for the population mean amount of gasoline contained in a standard 42-gallon barrel.

A. 42.15 ± 1.7109 (0.65) / 25

B. 42 ± 1.645 (0.65) / 5

C. 42 ± 1.7109 (0.65) / 25

D. 42.15 ± 1.645 (0.65) / 5

19. “Is live lecture over Zoom an effective way to conduct online lectures?” A pilot sample of 50 students of UM reveals that 18 of them gave a positive response. If a researcher wants to estimate the proportion of positive responses from all the students of UM, what should be the minimum sample size used if she wants the width of a 95% confidence interval estimate to be 0.10?

A. 355

B. 97

C. 385

D. 89

20. A dean of a business school is interested in determining whether the mean grade point average (GPA) of students is less than3.04. The population standard deviation is 0.41 A random sample of 200 students indicates a sample mean GPA of 2.94. A test is conducted at the 0.05 level of significance to determine whether the mean grade point average (GPA) of students is less than 3.04. What is the test statistic value in this test?

A. +0.244

B. –3.449

C. –0.244

D. +3.449

21.A random sample of 40 bags of flour is weighed. It is found that the sample mean is 453.08 grams. All weights of the bags of flour have a population standard deviation of 5.42 grams. What is the lower limit of an 80% confidence interval for the population mean weight?

A. 452.405 grams

B. 452.360 grams

C. 451.983 grams

D. No solution

Bardi Trucking Co., located in Cleveland, Ohio, makes deliveries in the Great Lakes region, the Southeast, and the Northeast. Jim Bardi, the president, is studying the relationship between the distance a shipment must travel and the length of time, in days, it takes the shipment to arrive at its destination. To investigate, Mr. Bardi selected a random sample of 20 shipments made last month. Shipping distance is the independent variable and shipping time is the dependent variable. The results are as follows:

Click here for the Excel Data File

1. Draw a scatter diagram. Based on these data, does it appear that there is a relationship between how many miles a shipment has to go and the time it takes to arrive at its destination?

1. On the graph below, use the point tool to plot the point corresponding to the first Distance and its Shipping Time (Distance 1).

2. Repeat the process for the remainder of the sample (Distance 2, Distance 3, … ).

3. To enter exact coordinates, double-click on the point and enter the exact coordinates of x and y.

1. b-1. Fill in the blanks. (Round your answers to 3 decimal places. Negative values should be indicated by minus sign.)

1. b-2. State the decision rule for 0.05 significance level: H₀: ρ ≤ 0; H₁: ρ > 0. (Round your answer to 3 decimal places.)

1. b-3. Compute the value of the test statistic. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.)

1. b-4. Can we conclude that there is a positive correlation between distance and time? Use the 0.05 significance level.

1. c-1. Determine the coefficient of determination. (Round your answer to 3 decimal places.)

1. c-2. Fill in the blank below. (Round your answer to 1 decimal place.)

4. Determine the standard error of estimate. (Round your answer to 3 decimal places.)

5. Would you recommend using the regression equation to predict shipping time?