Waiting times​ (in minutes) of customers at a bank where all customers enter a single waiting line and a bank where customers wait in individual lines at three different teller windows are listed below. Find the coefficient of variation for each of the two sets of​ data, then compare the variation. Bank A​ (single line): 6.5 6.6 6.7 6.8 7.1 7.4 7.4 7.6 7.7 7.8 Bank B​ (individual lines): 4.2 5.4 5.8 6.2 6.7 7.7   7.8 8.6 9.3 9.9

The coefficient of variation for the waiting times at Bank A is

nothing​%.

​(Round to one decimal place as​ needed.)

A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X₁ = median age in 2005, X₂ = number of 2005 bankruptcies per 1,000 people, X₃ = 2004 federal expenditures per capita, and X₄ = 2005 high school graduation percentage.

(a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.)

yˆy^ =  +  AgeMed +  Bankrupt +  FedSpend +  HSGrad%

(b-1) The 2005 state-by-state crime rate per 100,000

(b-2) The 2005 state-by-state crime rate per 100,000    

(b-3) The 2005 state-by-state crime rate per 100,000           

(b-4) The 2005 state-by-state crime rate per 100,000      

(c) Would the intercept seem to have meaning in this regression?

(d) Make a prediction for Burglary when X₁= 34 years, X₂= 7.2 bankruptcies per 1,000, X₃= $5,044, and X₄= 84 percent.

Burglary Rate

rev: 09_26_2016_QC_CS-62964, 09_20_2017_QC_CS-101173

A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies per 1,000 people, X3 = 2004 federal expenditures per capita, and X4 = 2005 high school graduation percentage. Predictor Coefficient Intercept 4,304.4610 AgeMed -26.903 Bankrupt 20.8921 FedSpend -0.0312 HSGrad% -29.1815 (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) yˆ =_____ + _____ AgeMed + _______ Bankrupt + _____ FedSpend + ______ HSGrad%

(b-1) The 2005 state-by-state crime rate per 100,000

increases by about 27 as the state median age increases.

decreases by about 27 as the state median age increases.

(b-2) The 2005 state-by-state crime rate per 100,000

decreases by about 21 for every 1,000 new bankruptcies filed.

increases by about 21 for every 1,000 new bankruptcies filed.

(b-3) The 2005 state-by-state crime rate per 100,000

decreases by 0.0312 for each dollar increase in federal funding per person.

increases by 0.0312 for each dollar increase in federal funding per person.

(b-4) The 2005 state-by-state crime rate per 100,000

decreases by about 29 for each 1% increase in high school graduations.

increases by about 29 for each 1% increase in high school graduations.

(c) Would the intercept seem to have meaning in this regression?

Yes No

(d) Make a prediction for Burglary when X1 = 30 years, X2 = 5.0 bankruptcies per 1,000, X3 = $5,723, and X4 = 80 percent.

(Round your answers to 4 decimal places.)

Burglary Rate $_______

A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X₁ = median age in 2005, X₂ = number of 2005 bankruptcies per 1,000 people, X₃ = 2004 federal expenditures per capita, and X₄ = 2005 high school graduation percentage.

(a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.)

yˆy^ =  +  AgeMed +  Bankrupt +  FedSpend +  HSGrad%

(b-1) The 2005 state-by-state crime rate per 100,000

(b-2) The 2005 state-by-state crime rate per 100,000    

(b-3) The 2005 state-by-state crime rate per 100,000           

(b-4) The 2005 state-by-state crime rate per 100,000      

(c) Would the intercept seem to have meaning in this regression?

(d) Make a prediction for Burglary when X₁= 34 years, X₂= 7.2 bankruptcies per 1,000, X₃= $5,044, and X₄= 84 percent.

Burglary Rate

rev: 09_26_2016_QC_CS-62964, 09_20_2017_QC_CS-1011

Thinking back to the “Practical Framework for Changing Behaviours” reading in module 1 (Health Communication Network, 2004), how do the constructs of the Health Belief Model and the Transtheoretical Model “fit” into the eight conditions that must be true for a person to perform that behavior?

Thinking back to the “Practical Framework for Changing Behaviours” reading in module 1 (Health Communication Network, 2004), how do the constructs of the Health Belief Model and the Transtheoretical Model “fit” into the eight conditions that must be true for a person to perform that behavior?

A manager for an insurance company believes that customers have the following preferences for life insurance products: 30 % prefer Whole Life, 30 % prefer Universal Life, and 40 % prefer Life Annuities. The results of a survey of 333 customers were tabulated. Is it possible to refute the sales manager's claimed proportions of customers who prefer each product using the data?

Product Number

Whole. 110

Universal 105

Annuities. 118

Step 1 of 10: State the null and alternative hypothesis.

Step 2 of 10: What does the null hypothesis indicate about the proportions of customers who prefer each insurance product?

Step 3 of 10: State the null and alternative hypothesis in terms of the expected proportions for each category.

Step 4 of 10: Find the expected value for the number of customers who prefer Whole Life. Round your answer to two decimal places.

Step 5 of 10: Find the expected value for the number of customers who prefer Universal Life. Round your answer to two decimal places.

Step 6 of 10: Find the value of the test statistic. Round your answer to three decimal places.

Step 7 of 10: Find the degrees of freedom associated with the test statistic for this problem.

Step 8 of 10: Find the critical value of the test at the 0.010.01 level of significance. Round your answer to three decimal places.

Step 9 of 10: Make the decision to reject or fail to reject the null hypothesis at the 0.010.01 level of significance.

Step 10 of 10: State the conclusion of the hypothesis test at the 0.010.01 level of significance.

Consider the following companies. Juventus F.C. S.p.A. is an Italian publicly listed football club. The club’s primary sources of revenue are: a Season and single ticket sales. b Television, radio, and media rights. c Sponsorship and advertising contracts. d The disposal of players’ registration rights. Players’ registration rights are recognized on the balance sheet at cost and amortized over the players’ contract terms. The club owns its stadium (“Juventus Stadium”), which opened in 2011, but leases the land adjacent to its stadium from the City of Turin under an operating lease arrangement. The operating lease has a term of 99 years and involves a lease payment, made in advance, of close to €12.8 million. To help finance the €105 million construction cost of the stadium, Juventus entered into an agreement with a large sports marketing agency, selling the exclusive naming rights for the new stadium for a period of 12 years. In exchange for the naming rights, Juventus received an advance payment of €38.5 million. Spyker Cars N.V. is a small Netherlands-based designer and manufacturer of exclusive sports cars, which had its initial public offering (IPO) in 2004 but delisted from the Amsterdam Stock Exchange in 2013. During the first five years as a publicly listed company, Spyker’s annual reve- nues ranged from €6.6 million (in 2009) to €19.7 million (in 2006). In these years, Spyker produced 242 new cars (including demonstration cars) and sold 194 cars. At the end of 2009, it held 28 cars in stock. Further, in 2009 the company spent close to €9.8 million on development, which it added to its development asset of €27.3 million, and €14,000 on research. Because Spyker had been loss-making since its IPO, the car manufacturer had €97 million in tax-deductible carry forward losses at the end of 2009. J. Sainsbury plc is a UK-based publicly listed retailer that operates 597 supermarkets and 707 convenience stores and has an estimated 16.7 percent market share in the UK. During the period 2010–2013, the company’s operating profit margin remained steady around 3.2 percent; in 2014 the operating profit margin dropped to 2.8 percent. At the end of March 2015, the net book value of Sainsbury’s land and buildings was £6.9 billion. A part of the company’s supermarket properties was pledged as security for long-term borrowings. In 2014 Sainsbury had 161,000 employees (107,000 full-time equivalents); many of them participated in one of the retailer’s defined-benefit pension plans.

1 Identify the key accounting policies for each of these companies.

2 What are these companies’ primary areas of accounting flexibility? (Focus on the key accounting policies.)