A company sells 100 computers for $300 each on account to a customer. The computer cost the company $125 each. The company recorded the revenue and cost of goods sold. The company allows customers a right of return which they estimate to be 2% of sales. Using the Financial Statement effects template, how should the company record the estimated returns?

Roberds Tech is a for-profit vocational school. The school bases its budgets on two measures of activity (i.e., cost drivers), namely student and course. The school uses the following data in its budgeting:

In March, the school budgeted for 1,770 students and 74 courses. The school's income statement showing the actual results for the month appears below:

Required:

Prepare a flexible budget performance report showing both the school's activity variances and revenue and spending variances for March. Label each variance as favorable (F) or unfavorable (U). (Indicate the effect of each variance by selecting "F" for favorable, "U" for unfavorable, and "None" for no effect (i.e., zero variance). Input all amounts as positive values.)

Using the existing regression equation, what would you predict the revenue of a team to be if the coach’s salary is .5 million and the winning percentage is 30 percent? Select one: a. 12 Million b. 14.8 Million c. 15.0 Million d. 14.2 Million e. Cannot be determined from the data.

A personal fitness company produces both a deluxe and a standard model of a smoothie blender for home use. Selling prices obtained from a sample of retail outlets follow.

(a)

The manufacturer's suggested retail prices for the two models show a $10 price differential. Use a 0.05 level of significance and test that the mean difference between the prices of the two models is $10.

Calculate the value of the test statistic. (Round your answer to three decimal places.)

Calculate the p-value. (Round your answer to four decimal places.)

(b)

What is the 95% confidence interval for the difference between the mean prices of the two models (in dollars)? (Round your answers to nearest cent. Use the mean price for the deluxe model − the mean price for the standard model.)

$ to $

p-value =

1. You have been asked to ascertain whether there is a relationship between income level and the amount of money donated to the campaign. Sample data concerning these two categorical variables is given in appendix three below. The numbers in the table represent the numbers of supporters in various income categories who have donated certain amounts of money. At both the 2% and 5% levels of significance, is there evidence of a statistical relationship between income level and amount of money donated to the campaign?

                                                            Income Level

Amount Donated <20K [20K,40) [40K,60K) [60K,80K) ≥80K

[$0,$50)                     35        30              18             10             22                      

[$50,$100                  12        25              26             9              18                      

[$100,$150)               6         20              27             7               5                       

[$150,$200)               7         16              25             10              8                       

[$200,$250)               9         8               11             16              7                                   

[$250,$300)               10        7                8              19             13                      

≥$300                         17        9                8              14             19

Discuss how the company could reduce the problem of customers terminating their pay-TV service after only three months.

Curtiss Construction Company, Inc., entered into a fixed-price contract with Axelrod Associates on July 1, 2018, to construct a four-story office building. At that time, Curtiss estimated that it would take between two and three years to complete the project. The total contract price for construction of the building is $4,540,000. Curtiss concludes that the contract does not qualify for revenue recognition over time. The building was completed on December 31, 2020. Estimated percentage of completion, accumulated contract costs incurred, estimated costs to complete the contract, and accumulated billings to Axelrod under the contract were as follows:

At 12-31-2018

At 12-31-2019

At 12-31-2020

Percentage of completion

10

%

60

%

100

%

Costs incurred to date

$

368,000

$

2,898,000

$

4,889,000

Estimated costs to complete

3,312,000

1,932,000

0

Billings to Axelrod, to date

729,000

2,350,000

4,540,000

Required:
1. Compute gross profit or loss to be recognized as a result of this contract for each of the three years.
2. Assuming Curtiss recognizes revenue over time according to percentage of completion, compute gross profit or loss to be recognized in each of the three years.
3. Assuming Curtiss recognizes revenue over time according to percentage of completion, compute the amount to be shown in the balance sheet at the end of 2018 and 2019 as either cost in excess of billings or billings in excess of costs.

1. Compute gross profit or loss to be recognized as a result of this contract for each of the three years. 2. Assuming Curtiss recognizes revenue over time according to percentage of completion, compute gross profit or loss to be recognized in each of the three years. (Leave no cells blank - be certain to enter "0" wherever required. Loss amounts should be indicated with a minus sign.)

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Year

Req 1 Gross Profit (Loss) Recognized ("Upon Completion")

Req 2 Gross Profit (Loss) Recognized ("Over Time")

2018

$0

$86,000

2019

$(290,000)

$(376,000)

2020

$(59,000)

$(86,000)

Total project profit (loss)

$(349,000)

$(376,000)

Req 3

2.Assuming Curtiss recognizes revenue over time according to percentage of completion, compute the amount to be shown in the balance sheet at the end of 2018 and 2019 as either cost in excess of billings or billings in excess of costs.

Balance Sheet (Partial)

2018

2019

Current assets:

Costs less loss in excess of billings

Current liabilities:

Billings in excess of costs and profit

$275,000

Please calculate Costs less loss in excess of billings in 2019.

We assume that our wages will increase as we gain experience and become more valuable to our employers. Wages also increase because of inflation. By examining a sample of employees at a given point in time, we can look at part of the picture. How does length of service (LOS) relate to wages? The data here (data162.dat) is the LOS in months and wages for 60 women who work in Indiana banks. Wages are yearly total income divided by the number of weeks worked. We have multiplied wages by a constant for reasons of confidentiality.

(a) Plot wages versus LOS. Consider the relationship and whether or not linear regression might be appropriate. (Do this on paper. Your instructor may ask you to turn in this graph.)

(b) Find the least-squares line. Summarize the significance test for the slope. What do you conclude? Wages = + LOS

t =

P =

(c) State carefully what the slope tells you about the relationship between wages and length of service.

(d) Give a 95% confidence interval for the slope.

Data Set:

worker  wages   los     size
1       42.3078 40      Large
2       44.0121 36      Small
3       46.122  51      Small
4       45.1671 28      Small
5       46.2362 18      Large
6       49.1255 43      Small
7       62.8503 70      Large
8       56.8422 27      Large
9       54.4156 42      Large
10      53.6614 34      Small
11      63.2144 148     Large
12      46.0673 21      Small
13      78.7749 99      Small
14      63.1945 52      Large
15      43.0515 58      Large
16      71.653  65      Large
17      54.0349 65      Large
18      37.814  73      Small
19      48.5537 55      Large
20      74.7885 103     Large
21      37.5076 95      Large
22      94.457  26      Small
23      59.3541 35      Large
24      37.7513 137     Small
25      56.1559 105     Large
26      65.174  110     Small
27      52.3183 111     Small
28      66.1117 64      Large
29      39.0966 27      Large
30      51.9956 74      Large
31      68.0974 59      Small
32      63.6235 29      Large
33      37.023  79      Large
34      44.9522 90      Small
35      46.7601 62      Large
36      49.0779 91      Large
37      41.1978 112     Large
38      68.2986 27      Small
39      48.9625 173     Large
40      51.6892 18      Small
41      68.4352 67      Small
42      71.5281 46      Small
43      56.7601 42      Large
44      55.8925 27      Small
45      62.2866 113     Large
46      49.8865 31      Small
47      58.8308 48      Large
48      44.7858 49      Large
49      57.2444 152     Small
50      60.0774 31      Large
51      44.075  41      Large
52      56.9571 18      Large
53      53.2775 42      Large
54      60.224  93      Small
55      55.9754 90      Small
56      40.8347 32      Large
57      55.0511 174     Small
58      51.142  59      Large
59      50.4712 38      Small
60      56.0068 19      Large

We assume that our wages will increase as we gain experience and become more valuable to our employers. Wages also increase because of inflation. By examining a sample of employees at a given point in time, we can look at part of the picture. How does length of service (LOS) relate to wages? The data here (data162.dat) is the LOS in months and wages for 60 women who work in Indiana banks. Wages are yearly total income divided by the number of weeks worked. We have multiplied wages by a constant for reasons of confidentiality.

(a) Plot wages versus LOS. Consider the relationship and whether or not linear regression might be appropriate. (Do this on paper. Your instructor may ask you to turn in this graph.)

(b) Find the least-squares line. Summarize the significance test for the slope. What do you conclude? Wages = + LOS

t =

P =

(c) State carefully what the slope tells you about the relationship between wages and length of service.

(d) Give a 95% confidence interval for the slope.

Data Set:

worker  wages   los     size
1       42.3078 40      Large
2       44.0121 36      Small
3       46.122  51      Small
4       45.1671 28      Small
5       46.2362 18      Large
6       49.1255 43      Small
7       62.8503 70      Large
8       56.8422 27      Large
9       54.4156 42      Large
10      53.6614 34      Small
11      63.2144 148     Large
12      46.0673 21      Small
13      78.7749 99      Small
14      63.1945 52      Large
15      43.0515 58      Large
16      71.653  65      Large
17      54.0349 65      Large
18      37.814  73      Small
19      48.5537 55      Large
20      74.7885 103     Large
21      37.5076 95      Large
22      94.457  26      Small
23      59.3541 35      Large
24      37.7513 137     Small
25      56.1559 105     Large
26      65.174  110     Small
27      52.3183 111     Small
28      66.1117 64      Large
29      39.0966 27      Large
30      51.9956 74      Large
31      68.0974 59      Small
32      63.6235 29      Large
33      37.023  79      Large
34      44.9522 90      Small
35      46.7601 62      Large
36      49.0779 91      Large
37      41.1978 112     Large
38      68.2986 27      Small
39      48.9625 173     Large
40      51.6892 18      Small
41      68.4352 67      Small
42      71.5281 46      Small
43      56.7601 42      Large
44      55.8925 27      Small
45      62.2866 113     Large
46      49.8865 31      Small
47      58.8308 48      Large
48      44.7858 49      Large
49      57.2444 152     Small
50      60.0774 31      Large
51      44.075  41      Large
52      56.9571 18      Large
53      53.2775 42      Large
54      60.224  93      Small
55      55.9754 90      Small
56      40.8347 32      Large
57      55.0511 174     Small
58      51.142  59      Large
59      50.4712 38      Small
60      56.0068 19      Large

A retailer of electronic equipment received six DVD players from the manufacturer. Three of the DVD players were damaged in the shipment. The retailer sold two DVD players to two customers. Consider the problem of calculating the probability that the customers receive damaged DVD players. [2] Can a binomial distribution be used for the solution of the above problem? Why or why not? [1] What kind of probability distribution can be used to solve this problem? [1] What is the probability that both customers received damaged DVD players? [1] What is the probability that only one of the two customers received a defective DVD player?