Q1. Which of the following statements is true? [1 mark]

1. Alpha Co owes its employees $5,000 at the year-end on Dec 31, 2014. Payment of the employees’ wages on Jan 3, 2015 will include a debit to wages expense, and credits to wages payable and cash.

2. Beta Co. purchased $5,000 worth of supplies in August and recorded the purchase in the Supplies account. On Dec 31, the fiscal year-end, $3,200 of the supplies remained. The Dec 31, year-end adjusting entry would include a debit of $2,800 to Supplies.

3. On June 30, Gamma Co. received $15,000 cash as a down payment on a 12-month consulting contract. Gamma recorded cash and recognized an appropriate liability. At year end on Dec 31, Gamma will debit consulting revenue for $7,500.

4. On Sept 1, Delta Co. paid $9,000 for a six-month insurance policy, debiting prepaid insurance. After making the appropriate adjusting entry on Dec 31, the prepaid insurance account would have a balance of $6,000.

5. On August 31, 2014, a company signed a $10,000 12 month, note payable bearing 6% interest pa. The company’s Dec 31, year-end adjusting entry should include a credit of $200 to interest payable.

Q2. Which of the following statements is true? [1 mark]

1. The 4 steps in closing are, close; (1) credit balances in revenue accounts to Income Summary; (2) credit balances in expense accounts to Income Summary; (3) Income Summary to Owner's Capital; (4) Withdrawals to Owner's Capital.

B.     Closing entries are designed to transfer the end-of-period balances in the revenue accounts, the expense accounts, and the withdrawals account to owner's capital.  

C.     Closing entries are required at the end of each accounting period to close all ledger accounts.

D.     Asset, liability, and revenue accounts are not closed while a company continues in business.

E.     The income summary account is used during the adjusting process to hold revenue, expenses, and withdrawals, before the net difference is added to or subtracted from the owner’s capital.

Q3. Which of the following statements is false? [1 mark]

1. The cash basis of accounting recognizes revenues when cash is received from customers.
2. The accrual basis of accounting recognizes expenses when they are incurred.
3. The cash basis of accounting requires adjustments to match expenses with revenues.
4. The accrual basis of accounting recognizes revenue when it is earned.
5. The cash basis of accounting recognizes expenses when cash is paid.
   

Q4. Which of the following is true? [1 mark]

1. When total debits equal the total credits in a trial balance it guarantees no errors were made.
2. Matching principle requires expenses to be recorded in the same accounting period as they are incurred.
3. Closing entries are necessary so that owner's capital will begin each period with a zero balance.
4. The last 4 steps in the accounting cycle include analyzing, journalizing, posting, and preparing a trial balance.
5. Temporary accounts accumulate financial data related to one period. Temporary accounts include revenue, expenses, accumulated depreciation, and withdrawals.

The following scenario is to be used to complete Case Study 2 – Regression Analysis. Please create your output in Excel, Copy it to Microsoft Word and answer the questions below. Everything should be in one word file. Please copy and paste the excel output created as the last page of the assignment, after the answers to the questions.

The owner of Showtime Movie Theaters, Inc., would like to estimate weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follows.

How many independent variables are there?

3 independent variables

List and label each independent variable (x?, x?, etc.)

X1 = Weekly gross revenue

X2= Television Advertising

X3= Newspaper advertising

Develop a simple linear regression equation using ONLY the amount of television as the independent variable. (Include this output)

Develop a simple linear regression equation using ONLY the newspaper advertising as the independent variable. (Include this output)

Develop a multiple regression equation using the amount of television and newspaper advertising as the independent variables. (Include this output)

Answer the following questions based on the multiple regression output ONLY!!

What is the proportion of variation in Weekly Gross Revenue due to television advertising and newspaper advertising?

What is the strength of the linear relationship between the amount of television, newspaper advertising and weekly gross revenue?

List the SSR, SSE, SST, MSR, MSE.

Give the value of F.

What is the p value for this regression model? P = (two decimal places)

Is this model useful? If so, why and if not, why not. If the model is useful, proceed to question 12.

If the model is useful, estimate the weekly gross revenue for a week when $3500 is spent on television advertising and $1800 is spent on newspaper advertising?

Are each of the variables good for the model? List their p values and explain your answer.

Need assistance on answering please

3. Relationship between tax revenues, deadweight loss, and demandelasticity

The government is considering levying a tax of $100 per unit on suppliers of either leather jackets or smartphones. The supply curve for each of these two goods is identical, as you can see on each of the following graphs. The demand for leather jackets is shown by DLDL (on the first graph), and the demand for smartphones is shown by DSDS (on the second graph).

Suppose the government taxes leather jackets. The following graph shows the annual supply and demand for this good. It also shows the supply curve (S+TaxS+Tax) shifted up by the amount of the proposed tax ($100 per jacket).

On the following graph, use the green rectangle (triangle symbols) to shade the area that represents tax revenue for leather jackets. Then use the black triangle (plus symbols) to shade the area that represents the deadweight loss associated with the tax.

Leather Jackets MarketTax RevenueDeadweight Loss050100150200250300350400450500550600240220200180160140120100806040200PRICE (Dollars per jacket)QUANTITY (Jackets)DLSupplyS+Tax

Instead, suppose the government taxes smartphones. The following graph shows the annual supply and demand for this good, as well as the supply curve shifted up by the amount of the proposed tax ($100 per phone).

On the following graph, do for smartphones the same thing you did previously on the graph for leather jackets. Use the green rectangle (triangle symbols) to shade the area that represents tax revenue for smartphones. Then, use the black triangle (plus symbols) to shade the area that represents the deadweight loss associated with the tax.

Smartphones MarketTax RevenueDeadweight Loss050100150200250300350400450500550600240220200180160140120100806040200PRICE (Dollars per phone)QUANTITY (Phones)DSSupplyS+Tax

Complete the following table with the tax revenue collected and deadweight loss caused by each of the tax proposals.

Suppose the government wants to tax the good that will generate more tax revenue at a lower welfare cost. In this case, it should tax   because, all else held constant, taxing a good with a relatively   elastic demand generates larger tax revenue and smaller deadweight loss.

1. Convert the following code shown below to C++ code:

A psychologist conducted an experiment analysing the relationship between student scores in an exam and the amount of attention they paid in class. The latter was measured using a type of brain monitor. The Psychologist believed that scores would increase by 1 for every two unit increase in attention. The data are listed in the excel spreadsheet.

Estimate a linear regression between the score (Y) and the measure of attention(X).

(a) Write out the equation for Y in the form , but with coefficients. Show the estimated standard errors in parenthesis below the coefficients. What is the R2 of the regression? Calculate a 99 percent confidence interval for β.                                                               [5 pts]

(b) What are the mean and the estimated standard deviation of the estimated residuals? [2 pts]

Hint: the first answer is definitional and the second answer is easily seen from the output.

(c )Test the hypothesis that there is no relationship between the variables at the 90 percent significance level.                                                                                                    [3 pts]

(d) Test the hypothesis that the coefficient β=0.5 at the 99% significance level.               [3 pts]

(e) The Psychologist concluded from the experiment that test scores increase significantly if students pay attention in class. In one word, how would you describe the results of this experiment based on the data you have?                                                                                                       [2 pts]

DATA:

A 0.500 g sample containing Ag2O and inert material is heated, causing the silver oxide to decompose according to the following equation:

2 Ag2O(s) → 4 Ag(s) + O2(g)

If 13.8 mL of gas are collected over water at 27°C and 1.00 atm external pressure, what is the percentage of silver oxide in the sample? The partial pressure of water is 26.7 mm Hg at 27°C.

a.) 25.1%

b.) 51.9%

c.)12.5%

d.) 50.1%

according to the US census bureau, the population of the US seniors65 and older, in the year 2004 was approximately 36,300,000 people. In the year 2010, it was 40,267,984 people. the senior population was growing at an approximately constant rate during this period.

(a)use this information to express the US senior population as a function of time since the year 2000.

(b) what is slope of your function? what does this mean in the context?

(c) what would this model indicate that the US population of seniors was in the year 2000? ( The actual population in that year was approximately 34,991,753)

(d) what does this model predict the US population of seniors to be for the 2020 census? Do you think this will be an overestimate or underestimate and why?

(e) when does your model predict the US population of senior to be 45,500,000 people?

The UW student-athletes on the women's teams compete in various NCAA-I sports. Each team may be regarded as a random sample of all the NCAA-I athletes in that sport. The 14 players listed on the roster for the 2004-05 Women’s Basketball team had an average height of 69.67 inches with a standard deviation of 3.47 inches. Give a 99% confidence interval for the average height of NCAA-I women’s basketball players in that year. Write a one or two sentence summary in non-statistical language to describe what you have found, not how you found it. Your audience is people who have never had a statistics class (think of middle of the road 8th graders, not the really bright ones).

Starting on September 1, 2000 - the day he starts college - and ending on September 1, 2004, Craig borrowed $6500 a year to pay for college expenses (i.e. that's 5 withdrawals total).
After graduation, he decided to go to graduate school in mathematics, and his loans were deferred (i.e. they accrued interest, but no payments were due). After finishing graduate school, he began repaying his loans. Beginning on July 1, 2007, he made monthly payments for 8 years. Each payment increased by 2.6% over the previous payment. If his loans had a fixed nominal rate of 6% convertible monthly for the entire life of the loans, what was the size of his first payment?

Answer = $

Starting on September 1, 2000 - the day he starts college - and ending on September 1, 2004, Craig borrowed $4000 a year to pay for college expenses (i.e. that's 5 withdrawals total).
After graduation, he decided to go to graduate school in mathematics, and his loans were deferred (i.e. they accrued interest, but no payments were due). After finishing graduate school, he began repaying his loans. Beginning on July 1, 2007, he made monthly payments for 11 years. Each payment increased by 1.5% over the previous payment. If his loans had a fixed nominal rate of 6.6% convertible monthly for the entire life of the loans, what was the size of his first payment?