1.

On January 1, Year 1, Milton Manufacturing Company purchased equipment with a list price of $27,000. A total of $2000 was paid for installation and testing. During the first year, Milton paid $3000 for insurance on the equipment and another $600 for routine maintenance and repairs. Milton uses the units-of-production method of depreciation. Useful life is estimated at 100,000 units, and estimated salvage value is $4000. During Year 1, the equipment produced 14,000 units. What is the amount of depreciation for Year 1?

Group of answer choices

$3920

$4480

$4004

$3500

2.

On January 1, Year 1, Missouri Co. purchased a truck that cost $44,000. The truck had an expected useful life of 10 years and a $4000 salvage value. Missouri uses the double declining-balance method. What is the amount of depreciation expense recognized in Year 2?

Group of answer choices

$6400

$4400

$8800

$7040

3.

On January 1, Year 1, Friedman Company purchased a truck that cost $53,000. The truck had an expected useful life of 8 years and an $9000 salvage value. Friedman uses the double-declining-balance method. What is the book value of the truck at the end of Year 1? (Do not round intermediate calculations.)

Group of answer choices

$42,000

$33,000

$30,750

$39,750

4.

On January 1, Year 1, Friedman Company purchased a truck that cost $44,000. The truck had an expected useful life of 100,000 miles over 8 years and an $8000 salvage value. During Year 2, Friedman drove the truck 22,000 miles. Friedman uses the units-of-production method. What is depreciation expense in Year 2? (Do not round intermediate calculations.):

Group of answer choices

$5500

$9680

$7920

$4500

Question 1

The mean starting salary of job with certain degree is unknown. Based on a sample of starting salary of 25 employees, the mean salary turns out to be $45,750/year. Assume that the population of all starting salaries follows a normal distribution with standard deviation $9125.

To find a 95% confidence interval estimate of mean staring salary, what interval estimate will you use?

Group of answer choices

T-interval

Z-interval

Question 2

The mean starting salary of job with certain degree is unknown. Based on a sample of starting salary of 25 employees, the mean salary turns out to be $45,750/year. Assume that the population of all starting salaries follows a normal distribution with standard deviation $9125.

Find a 95% confidence interval estimate of mean staring salary.

Group of answer choices

(42748, 48752)

(42173, 49327)

(41659,49841)

Question 3

The average speed of all cars passing though a certain road is unknown. The following data refers to the speed, measured in miles/hour, for a sample of 9 cars passing through the road on a given day.

We wish to find a 95% confidence interval of mean speed of all cars passing through the road.

What confidence interval will be appropriate for this problem?

Group of answer choices

T-interval

Z-interval

Question 4

The average speed of all cars passing though a certain road is unknown. The following data refers to the speed, measured in miles/hour, for a sample of 9 cars passing through the road on a given day.

Find a 95% confidence interval of mean speed of all cars passing through the road.

Group of answer choices

(42.47, 53.30)

(43.35, 52.43)

(44,23, 51.55)

Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg). x 29 43 30 47 23 40 34 52 y 30 22 23 13 29 17 21 14

Complete parts (a) through (e), given Σx = 298, Σy = 169, Σx2 = 11,788, Σy2 = 3849, Σxy = 5906, and r ≈ −0.889.

(a) Draw a scatter diagram displaying the data.

(b) Verify the given sums Σx, Σy, Σx2, Σy2, Σxy, and the value of the sample correlation coefficient r. (Round your value for r to three decimal places.) Σx = Σy = Σx2 = Σy2 = Σxy = r =

(c) Find x, and y. Then find the equation of the least-squares line y hat = a + bx. (Round your answers for x and y to two decimal places. Round your answers for a and b to three decimal places.) x = y = y hat = + x (

d) Graph the least-squares line. Be sure to plot the point (x, y) as a point on the line. WebAssign Plot WebAssign Plot WebAssign Plot WebAssign Plot

(e) Find the value of the coefficient of determination r2. What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for r2 to three decimal places. Round your answers for the percentages to one decimal place.) r2 = explained % unexplained % (f) Suppose a car weighs x = 45 (hundred pounds). What does the least-squares line forecast for y = miles per gallon? (Round your answer to two decimal places.) mpg

Use the data set named Store_Visits located in the folder Data Files for HW Assignment (outside of Minitab folder) in the K-drive. The response variable y is the number of visits of a customer to a particular food store in a large suburban area within the period of a month, and the independent variable x is the distance (in miles) of the customer’s home to the store.

Fit a simple linear regression model to the data, and answer the following questions.

a) Give the proportion of the variation in the number of visits per month of a customer explained by the distance of the customer’s home to the store.

b) Submit the residual plot. ^ It appears from the plot that there is a problem with one of the model assumptions. Which one is it, and what would you suggest to remedy the problem?

2. c) Carry out your suggestion to fix the problem of part (b) and submit a new residual plot. Does your suggested remedy work? ^

3. d) Based on your new model, what is the proportion of the variation in the number of visits per month of a customer explained by the distance of the customer’s home to the store? How does it compare to that of the original model?

4. e) Based on your new model, construct a 95% prediction interval for y, the number of visits to the store for a customer who lives 2.5 miles from the store. Interpret the P.I.

K-Drive data. -Minitab

y   x
12   0.8
5   1.2
6   2.3
8   1.5
3   3.2
2   6.3
1   7.9
2   5.3
6   1.5
3   1.9
10   1.7
5   2.6
3   2.9
6   4.2
2   3.9
4   3.1
3   5.8
6   1.7
7   2.2
2   4.5
1   6.1
1   5.8
1   7.4
3   6.4
2   4.7
2   3.9
3   4
4   4.6

Use the data set named Store_Visits located in the folder Data Files for HW Assignment (outside of Minitab folder) in the K-drive. The response variable y is the number of visits of a customer to a particular food store in a large suburban area within the period of a month, and the independent variable x is the distance (in miles) of the customer’s home to the store.

Fit a simple linear regression model to the data, and answer the following questions.

a) Give the proportion of the variation in the number of visits per month of a customer explained by the distance of the customer’s home to the store.

b) Submit the residual plot. ^ It appears from the plot that there is a problem with one of the model assumptions. Which one is it, and what would you suggest to remedy the problem?

2. c) Carry out your suggestion to fix the problem of part (b) and submit a new residual plot. Does your suggested remedy work? ^

3. d) Based on your new model, what is the proportion of the variation in the number of visits per month of a customer explained by the distance of the customer’s home to the store? How does it compare to that of the original model?

4. e) Based on your new model, construct a 95% prediction interval for y, the number of visits to the store for a customer who lives 2.5 miles from the store. Interpret the P.I.

K-Drive data. -Minitab

y   x
12   0.8
5   1.2
6   2.3
8   1.5
3   3.2
2   6.3
1   7.9
2   5.3
6   1.5
3   1.9
10   1.7
5   2.6
3   2.9
6   4.2
2   3.9
4   3.1
3   5.8
6   1.7
7   2.2
2   4.5
1   6.1
1   5.8
1   7.4
3   6.4
2   4.7
2   3.9
3   4
4   4.6

Swifty Company purchased a delivery truck for $26,000 on January 1, 2020. The truck has an expected salvage value of $1,000, and is expected to be driven 100,000 miles over its estimated useful life of 10 years. Actual miles driven were 12,800 in 2020 and 12,000 in 2021.

Calculate depreciation expense per mile under units-of-activity method. (Round answer to 2 decimal places, e.g. 0.50.)

eTextbook and Media

List of Accounts

Compute depreciation expense for 2020 and 2021 using (1) the straight-line method, (2) the units-of-activity method, and (3) the double-declining-balance method. (Round depreciation cost per unit to 2 decimal places, e.g. 0.50 and depreciation rate to 0 decimal places, e.g. 15%. Round final answers to 0 decimal places, e.g. 2,125.)

eTextbook and Media

List of Accounts

Assume that Swifty uses the straight-line method. Prepare the journal entry to record 2020 depreciation. (Credit account titles are automatically indented when amount is entered. Do not indent manually. If no entry is required, select "No Entry" for the account titles and enter 0 for the amounts. Round answers to 0 decimal places, e.g. 2,125.)

eTextbook and Media

List of Accounts

Assume that Swifty uses the straight-line method. Show how the truck would be reported in the December 31, 2020, balance sheet. (Round answers to 0 decimal places, e.g. 2,125.)

MAT 152 Lab 4   

Show your work, where appropriate. Remember that you do not have to show any work for what you enter into your graphing calculator.

CITY is the city fuel consumption in miles per gallon and HWY is the highway fuel consumption in miles per gallon.

For parts A – C, find each of them. (There is no work required since your graphing calculator gives you these values.)                  Round each number to 3 decimal places.  

1. the linear regression equation:

2.    the correlation coefficient, r:

3. the coefficient of determination, r2:

4. Interpret r by explaining this value (from #2 above) in a COMPLETE sentence.
   

There is a _______________ _______________ linear correlation between city and

Choose strong or weak.    Choose positive or negative.

highway fuel consumption.

5. Interpret r2 by explaining this value (from #3 above) in a COMPLETE sentence by filling in the blanks:

_________ % of the variation in _______________ mileage can be explained by the

                Change r2 to a %.                                  Choose city or highway.

                regression equation.

            _________% of the variation is unexplained.

6. Determine if there is a significant linear relationship between city and highway fuel consumption at α=0.05 by completing the hypothesis test steps below.                                                                                                                                                 (Use LinRegTTest.)   

1. H₀:

H_a:

2. Calculate the test statistic: t = ___________                  Round to 3 decimal places.

3. Calculate the p-value: ____________                              Round to 4 decimal places.

4. Select the correct decision: Reject H₀                 or         Fail to Reject H₀

5. Conclusion: (Explain in terms of if there is a significant linear relationship or not).

Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg).
x 27 42 31 47 23 40 34 52

y 33 21 24 13 29 17 21 14

Complete parts (a) through (e), given Σx = 296, Σy = 172, Σx2 = 11,652, Σy2 = 4042, Σxy = 5917, and r ≈ −0.911. (a) Draw a scatter diagram displaying the data.

(b) Verify the given sums Σx, Σy, Σx2, Σy2, Σxy, and the value of the sample correlation coefficient r. (Round your value for r to three decimal places.)

Σx =2 Σy =3 Σx2 =4 Σy2 =5 Σxy =6 r =7

(c) Find x, and y. Then find the equation of the least-squares line = a + bx. (Round your answers for x and y to two decimal places. Round your answers for a and b to three decimal places.) x = ___ y = ___ = y____ + ____x

(d) Graph the least-squares line. Be sure to plot the point (x, y) as a point on the line.

(e) Find the value of the coefficient of determination r2. What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for r2 to three decimal places. Round your answers for the percentages to one decimal place.)

r2 = _______ explained _____ % unexplained ______ %

(f) Suppose a car weighs x = 39 (hundred pounds). What does the least-squares line forecast for y = miles per gallon? (Round your answer to two decimal places.) ________mpg

Green Thumb Gardening is a small gardening service that uses activity-based costing to estimate costs for pricing and other purposes. The proprietor of the company believes that costs are driven primarily by the size of customer lawns, the size of customer garden beds, the distance to travel to customers, and the number of customers. In addition, the costs of maintaining garden beds depends on whether the beds are low maintenance beds (mainly ordinary trees and shrubs) or high maintenance beds (mainly flowers and exotic plants). Accordingly, the company uses the five activity cost pools listed below:

The company already has completed its first stage allocations of costs and has summarized its annual costs and activity as follows:

As the auditor of Komsu Air Limited (KAL) that manufactures and installs large commercial airconditioning systems. KAL typically has two or three large contracts (ranging from $6 million to $10 million each) in progress at any one time. The contracts usually take up to six months to complete, although unexpected on-site difficulties can result in lengthy delays in completion (of up to 12 months). KAL finances its operations with a mixture of equity, long-term debt (secured by fixed assets) and short-term bank loans.

It is now May 2017 and your planning of the audit of KAL for the year ended 30 June 2017 is nearing completion. You have met with the management of KAL and, from those discussions and a review of the preliminary information provided by KAL, you have identified several issues that may have implications for the company’s ability to continue as a going concern. The relevant issues are as follows:

 Competition in the industry is becoming more intense, with some customers now installing their own systems.

 KAL’s bank has requested cash flow forecasts for the coming year to support the short-term loans. It has indicated that it may need to withdraw funding or restructure debt if the forecasts are not adequate. The review of work-in-progress indicates that all the contracts in progress at year end are due for completion within six months of the balance date. There are no new contracts in place for the coming year, although management has indicated that there are orders currently being negotiated. The nature of the business is such that sales will fluctuate considerably from year to year depending on the timing of one or two large contracts.

 Assets consist chiefly of plant and equipment, some of which is specialised to the industry. Debtors are significant, but recoverability is not considered an issue as the ongoing projects are with reputable customers and management is not aware of any problems. Creditor balances are at normal levels, and the company is in a positive working capital position.

 Included in provisions is a large provision for warranty for one of KAL’s jobs completed at a hotel two years ago. It appears that the air-conditioning system is still not working and the hotel is now requesting a substantial refund of the contract price.

Required:

Explain whether you believe the area of going concern should be assessed as high risk and mitigating factors for KAL’s audit for the year ended 30 June 2017. (10 marks, maximum 300 words)