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

The postanesthesia care area (recovery room) at St. Luke’s Hospital in Maumee, Ohio, was recently enlarged. The hope was that the change would increase the mean number of patients served per day to more than 25. A random sample of 15 days revealed the following numbers of patients.

At the 0.01 significance level, can we conclude that the mean number of patients per day is more than 25?

  Click here for the Excel Data File

1. What is the decision rule? (Round your answer to 3 decimal places.)

2. Compute the value of the test statistic. (Round your answer to 3 decimal places.)

3. What is your decision regarding H₀?

4. Estimate the p-value.

The following is the post-closing trial balance for the Whitlow Manufacturing Corporation as of December 31, 2017.

The following transactions occurred during January 2018:

Post the transactions into the appropriate T-accounts. (Enter the date of the transaction in the column next to the amount. Be sure to include beginning balances.)

T accounts to use

cash

accounts receivable

inventory

equipment

accumulated depreciation- equipment

accounts payable

common stock

retained earnings

sales revenue

COGS

rent expense

salaries and wages expense

advertising expense

Standart represantation of Galois Field (27)

Rocky Guide Service provides guided 1–5 day hiking tours throughout the Rocky Mountains. Wilderness Tours hires Rocky to lead various tours that Wilderness sells. Rocky receives $1,900 per tour day, and shortly after the end of each month Rocky learns whether it will receive a $190 bonus per tour day it guided during the previous month if its service during that month received an average evaluation of "excellent" by Wilderness customers. The $1,900 per day and any bonus due are paid in one lump payment shortly after the end of each month.

• On July 1, based on prior experience, Rocky estimated there is a 40% chance it will earn the bonus for July tours. It guided a total of 10 days from July 1–July 15.
• On July 16, based on Rocky’s view that it had provided excellent service during the first part of the month, Rocky revised its estimate to an 90% chance it would earn the bonus for July tours. Rocky also guided customers for 15 days from July 16–July 31.
• On August 5 Rocky learned it did not receive an average evaluation of “excellent” for its July tours, so it would not receive any bonus for July, and received all payment due for the July tours.

Rocky bases estimates of variable consideration on the expected value it expects to receive.

1.) Prepare Rocky's July 15 journal entry to record revenue for tours given from July 1 - July 15

2.) Prepare Rocky's July 31 journal entry to record revenue for tours given from July 16 - July 31 and any adjustment needed for July 1 – July 15

3.) Prepare Rocky's August 5 journal entry to record the receipt of payment from Wilderness

4.) Prepare Rocky's August 5 journal entry to record any necessary adjustments to revenue

[The following information applies to the questions displayed below.]
Vanishing Games Corporation (VGC) operates a massively multiplayer online game, charging players a monthly subscription of $13. At the start of January 2018, VGC’s income statement accounts had zero balances and its balance sheet account balances were as follows:

In addition to the above accounts, VGC’s chart of accounts includes the following: Service Revenue, Salaries and Wages Expense, Advertising Expense, and Utilities Expense. The following transactions occurred during the January month:

1. Received $57,500 cash from customers on 1/1 for subscriptions that had already been earned in 2017.
2. Purchased 10 new computer servers for $42,800 on 1/2; paid $16,400 cash and signed a three-year note for the remainder owed.
3. Paid $15,300 for an Internet advertisement run on 1/3.
4. On January 4, purchased and received $3,250 of supplies on account.
5. Received $205,000 cash on 1/5 from customers for service revenue earned in January.
6. Paid $3,250 cash to a supplier on January 6.
7. On January 7, sold 17,300 subscriptions at $13 each for services provided during January. Half was collected in cash and half was sold on account.
8. Paid $400,000 in wages to employees on 1/30 for work done in January.
9. On January 31, received an electric and gas utility bill for $6,300 for January utility services. The bill will be paid in February.

2. Prepare journal entries for the January transactions. (If no entry is required for a transaction/event, select "No Journal Entry Required" in the first account field.)
3. Enter the beginning balances shown above in the following T-accounts and post the journal entries.
4. Prepare an unadjusted trial balance as of January 31, 2018.

The mean amount purchased by each customer at Churchill’s Grocery Store is $27 with a standard deviation of $9. The population is positively skewed. For a sample of 48 customers, answer the following questions:

a. What is the likelihood the sample mean is at least $29? (Round the z-value to 2 decimal places and the final answer to 4 decimal places.)

b. What is the likelihood the sample mean is greater than $26 but less than $29? (Round the z-value to 2 decimal places and the final answer to 4 decimal places.) c. Within what limits will 98% of the sample means occur? (Round the final answers to 2 decimal places.)