| REVISION EXERCISES | |||
| ACCOUNTS CLASSIFICATION AND NORMAL BALANCE OF ACCOUNTS | NAME: | ||
| Accounts name | Assets/Liabilities/Equity/income/Expense | normal balance | |
| (DR/CR) | |||
| 1 | Cash at Bank | ||
| 2 | Loan Payable | ||
| 3 | Interest payable | ||
| 4 | Salaries expense | ||
| 5 | Prepaid insurance | ||
| 6 | Accounts receivable | ||
| 7 | Office equipment | ||
| 8 | Accumulated depreciation-office equipment | ||
| 9 | Advertising expense | ||
| 10 | Depreciation expense-office equipment | ||
| 11 | Electricity expense | ||
| 12 | Land | ||
| 13 | Salaries payable | ||
| 14 | Building | ||
| 15 | Accumulated depreciation-building | ||
| 16 | Goodwill | ||
| 17 | Sales revenue | ||
| 18 | Interest income | ||
| 19 | Marketing expenses | ||
| 20 | Inventory | ||
| 21 | Allowance for doubtful debts | ||
| 22 | Utilities expense | ||
| 23 | Unearned revenue | ||
| 24 | Insurance expense | ||
| 25 | Rent expense | ||
| 26 | Ordinary share | ||
| 27 | Retained earnings/profit | ||
| TOTAL MARKS | |||
In: Accounting
Gatti Corporation reported the following balances at June
30.
| Accounts Payable | $110 |
| Accounts Receivable | 85 |
| Accumulated Depreciation—Equipment | 36 |
| Cash | 13 |
| Cash Equivalents | 18 |
| Contributed Capital | 130 |
| Depreciation Expense | 25 |
| Dividends | 7 |
| Equipment | 330 |
| Notes Payable (long-term) | 90 |
| Notes Payable (short-term) | 50 |
| Petty Cash | 10 |
| Restricted Cash (short-term) | 30 |
| Retained Earnings | 27 |
| Salaries and Wages Expense | 415 |
| Service Revenue | 510 |
| Deferred Revenue | 43 |
| Utilities Expense | 63 |
Required:
1. What amount should be reported as Cash and Cash
Equivalents?
2. Prepare a classified balance sheet. Do not show the
components that add up to your answer in requirement 1 but rather
show only the line Cash and Cash Equivalents. (Amounts to
be deducted should be indicated by a minus
sign.)
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Question 3 of 4 Total
In: Accounting
In: Biology
Copier maintenance. The Tri-City Office Equipment Corporation sells an imported copier on a franchise basis and performs preventive maintenance and repair service on this copier. The data below have been collected from 45 recent calls on users to perform routine preventive maintenance service; for each call, X is the number of copiers serviced and Y is the total number of minutes spent by the service person. Assume that first-order regression model (1.1) is appropriate. (a) Obtain the estimated regression function. (b) Plot the estimated regression function and the data. How well does the estimated regression function fit the data? (c) Interpret b o in your estimated regression function. Does b o provide any relevant information here? Explain. (d) Obtain a point estimate of the mean service time when X = 5 copiers are serviced. Use R programming . The data set is 20 2 60 4 46 3 41 2 12 1 137 10 68 5 89 5 4 1 32 2 144 9 156 10 93 6 36 3 72 4 100 8 105 7 131 8 127 10 57 4 66 5 101 7 109 7 74 5 134 9 112 7 18 2 73 5 111 7 96 6 123 8 90 5 20 2 28 2 3 1 57 4 86 5 132 9 112 7 27 1 131 9 34 2 27 2 61 4 77 5
In: Math
(please provide detailed solution with formula and figures)
the researcher wishes to use numerical descriptive measures to summarize the data on each of the two variables: hours worked per week and yearly income. a) Prepare and display a numerical summary report for each of the two variables including summary measures such as mean, median, range, variance, standard deviation, smallest and largest values and the three quartiles. Notes: Use QUARTILE.EXC command to generate the three quartiles. b) Compute the correlation coefficient using the relevant Excel function to measure the direction and strength of the linear relationship between the two variables. Display and interpret the correlation value.
|
Hours Per Week |
Yearly Income ('000's) |
|
18 |
43.8 |
|
13 |
44.5 |
|
18 |
44.8 |
|
25.5 |
46.0 |
|
11.5 |
41.2 |
|
18 |
43.3 |
|
16 |
43.6 |
|
27 |
46.2 |
|
27.5 |
46.8 |
|
30.5 |
48.2 |
|
24.5 |
49.3 |
|
32.5 |
53.8 |
|
25 |
53.9 |
|
23.5 |
54.2 |
|
30.5 |
50.5 |
|
27.5 |
51.2 |
|
28 |
51.5 |
|
26 |
52.6 |
|
25.5 |
52.8 |
|
26.5 |
52.9 |
|
33 |
49.5 |
|
15 |
49.8 |
|
27.5 |
50.3 |
|
36 |
54.3 |
|
27 |
55.1 |
|
34.5 |
55.3 |
|
39 |
61.7 |
|
37 |
62.3 |
|
31.5 |
63.4 |
|
37 |
63.7 |
|
24.5 |
55.5 |
|
28 |
55.6 |
|
19 |
55.7 |
|
38.5 |
58.2 |
|
37.5 |
58.3 |
|
18.5 |
58.4 |
|
32 |
59.2 |
|
35 |
59.3 |
|
36 |
59.4 |
|
39 |
60.5 |
|
24.5 |
56.7 |
|
26 |
57.8 |
|
38 |
63.8 |
|
44.5 |
64.2 |
|
34.5 |
55.8 |
|
34.5 |
56.2 |
|
40 |
64.3 |
|
41.5 |
64.5 |
|
34.5 |
64.7 |
|
42.3 |
66.1 |
|
34.5 |
72.3 |
|
28 |
73.2 |
|
38 |
74.2 |
|
31.5 |
68.5 |
|
36 |
69.7 |
|
37.5 |
71.2 |
|
22 |
66.3 |
|
33.5 |
66.5 |
|
37 |
66.7 |
|
43.5 |
74.8 |
|
20 |
62.0 |
|
35 |
57.3 |
|
24 |
55.3 |
|
20 |
56.1 |
|
41 |
61.5 |
In: Statistics and Probability
4. the researcher wishes to use numerical descriptive measures to summarize the data on each of the two variables: hours worked per week and income earned per year.
Notes: Use QUARTILE.EXC command to generate the three quartiles.
Compute the correlation coefficient using the relevant Excel function to measure the direction and strength of the linear relationship between the two variables. Display and interpret the correlation value.
Data of Hours worked and yearly income as below
| Yearly Income ('000's) | Hours Per Week |
| 43.8 | 18 |
| 44.5 | 13 |
| 44.8 | 18 |
| 46.0 | 25.5 |
| 41.2 | 11.5 |
| 43.3 | 18 |
| 43.6 | 16 |
| 46.2 | 27 |
| 46.8 | 27.5 |
| 48.2 | 30.5 |
| 49.3 | 24.5 |
| 53.8 | 32.5 |
| 53.9 | 25 |
| 54.2 | 23.5 |
| 50.5 | 30.5 |
| 51.2 | 27.5 |
| 51.5 | 28 |
| 52.6 | 26 |
| 52.8 | 25.5 |
| 52.9 | 26.5 |
| 49.5 | 33 |
| 49.8 | 15 |
| 50.3 | 27.5 |
| 54.3 | 36 |
| 55.1 | 27 |
| 55.3 | 34.5 |
| 61.7 | 39 |
| 62.3 | 37 |
| 63.4 | 31.5 |
| 63.7 | 37 |
| 55.5 | 24.5 |
| 55.6 | 28 |
| 55.7 | 19 |
| 58.2 | 38.5 |
| 58.3 | 37.5 |
| 58.4 | 18.5 |
| 59.2 | 32 |
| 59.3 | 35 |
| 59.4 | 36 |
| 60.5 | 39 |
| 56.7 | 24.5 |
| 57.8 | 26 |
| 63.8 | 38 |
| 64.2 | 44.5 |
| 55.8 | 34.5 |
| 56.2 | 34.5 |
| 64.3 | 40 |
| 64.5 | 41.5 |
| 64.7 | 34.5 |
| 66.1 | 42.3 |
| 72.3 | 34.5 |
| 73.2 | 28 |
| 74.2 | 38 |
| 68.5 | 31.5 |
| 69.7 | 36 |
| 71.2 | 37.5 |
| 66.3 | 22 |
| 66.5 | 33.5 |
| 66.7 | 37 |
| 74.8 | 43.5 |
| 62.0 | 20 |
| 57.3 | 35 |
| 55.3 | 24 |
| 56.1 | 20 |
| 61.5 | 41 |
In: Statistics and Probability
You may use Microsoft access or Derby DB
Please I need an answer for this problem, I have posted this problem 5 times.
Put aggregate without condition for the following 6 queries:
Queries:
-- Query 1
-- Find the details of students who was born after 31st december
2004.
select * from Student_Information where DOB>"2004-12-31";
-- Query 2
-- Find all student details whose first name begins with J.
select * from Student_Information where FirstName like 'J%';
-- Query 3
-- Find the total fees for each FeeID.
select FeeID,(OrientationFee+CampusFee+LabFee+CommencementsFee) as
"Total Fees" from Fees;
-- Query 4
-- Find all subject IDs whose Subject1 is botany.
select subjectID from Subjects where Subject1="Botany";
-- Query 5
-- Find all gradeIDs with 10 points for both quiz and exam.
select GradeID from Grades where Quizzes=10 and exams=10;
-- Query 6
-- Find the feeid and orientation fees where orientation fees is
beween 500 and 1300
select FeeId,OrientationFee from Fees where OrientationFee BETWEEN
500 AND 1300;
Schema:
Student's Information
Fees
Subjects
Grades
Student’s Information (ID, Firstname, Lastname, DOB);
Fees (ID, Orientationfees, Campusfees, Labfees, Commencementfees);
Subjects (ID, Subject1, Subject2, Subject3, Subject4);
Grades (ID, Quizzes, Classwork, Homework, Exams, Finalgrade);
Student's Information
|
ID |
Firstname |
Lastname |
DOB |
Fees
|
ID |
Orientationfees |
Campusfees |
Labfees |
Commencementfees |
Subjects
|
ID |
Subjectname |
Grades
|
ID |
Quizzes |
Classwork |
Homework |
Exams |
Finalgrade |
In: Computer Science
A study is conducted to determine the relationship between a driver's age and the number of accidents he or she has over a 1-year period. The data are shown here. If there is a significant relationship, predict the number of accidents of a driver who is 28.
| Driver's | No. of |
| Age x | accidents y |
| 16 | 3 |
| 24 | 2 |
| 18 | 5 |
| 17 | 2 |
| 23 | 0 |
| 27 | 1 |
| 32 | 1 |
For steps 4 and 5 of the hypothesis testing, what is your decision?
Select one:
a. Fail to reject H0. There is no relationship between the variables.
b. Reject H0. There is a significant relationship between the variables.
c. Fail to reject H0. The means are the same.
d. Reject H0. There is no relationship between the variables.
In: Statistics and Probability
A cinema has a single ticket counter that is manned by a cashier. The cashier is capable to handle 280 customers in an hour. Customers arrive at the counter at the rate of four customers per minute. Daniel, the owner who studied queuing models feels that all the seven assumptions for a single-channel model are met. By assuming Exponential service times and Poisson arrival rate, answer the following questions.
a) State three assumptions mentioned above.
b) Determine the average number of customers waiting to buy ticket.
c) Determine the percentage of time the cashier is free.
d) Calculate the average time spent by each customer in the system.
e) Calculate the average time each customer needs to spend waiting to buy ticket.
f) The management of the theatre is planning to increase the number of counters if the probability of the system is busy is higher than 0.5. Is it necessary to increase the number of counters?
In: Operations Management
A manager believes his restaurant follows infinite waiting line system. He has five servers, the customer arrival rate is 6 per hour, and the serving takes 20 minutes in average.
a. Determine the average number of customers waiting for service.
b. Compute the utilization of the system.
c. Compute the average time in the restaurant in minute.
d. compute the average number of customers in the restaurant.
e. Determine the average waiting time in line in minutes if just three servers are available.
In: Operations Management