A researcher working for an insurance company that sells life insurance would like to use regression analysis to predict life expectancy of his clients. He knows that there are several factors that contribute to life expectancy: some are genetic, some are related to life style, some are related to biological factors, and some are related to environment (access to health care, cleanliness of air, etc.) . He selects these candidate variables to develop his regression equation: gender, number of cigarettes smoked per day, cholesterol level, systolic blood pressure, and height-to-weight index: (actual weight / appropriate weight given gender, build, and height) * 100. Use the datasheet life expectancy in datasetsRM.xls to develop a regression equation to predict how long a person should live (for gender: 0=female, 1=male): 1. First, plot each non-categorical predictor variable against the dependent variable (age of death) and examine the plot to see if the relationship is linear. What’s your assessment? 2. Perform a multiple regression analysis and write up the results of your regression analysis in APA style. 3. For a male who does not smoke cigarettes at all, has a systolic blood pressure of 130, a height-to-weight index of 110, and a cholesterol level of 200, what is his life expectancy? NumCigsDay WtHtIndex Gender Cholesterol BloodPres AgeOfDeath 0 98 0 179 120 90 0 90 0 186 100 98 0 140 0 190 130 90 3 96 0 191 120 87 0 120 0 200 120 90 0 100 0 187 120 94 0 130 0 190 110 96 4 92 0 191 110 83 5 110 0 200 110 79 5 193 0 210 120 79 10 107 0 215 130 77 0 117 0 227 140 80 0 128 0 240 130 99 15 179 0 230 150 68 10 150 0 240 160 70 5 100 0 245 120 79 8 112 0 260 130 76 10 150 0 275 140 67 8 121 0 280 130 72 0 90 1 210 120 85 0 100 1 187 100 94 0 130 1 179 130 88 10 92 1 183 120 72 0 119 1 184 120 89 0 110 1 189 120 80 2 120 1 192 110 87 6 100 1 196 110 69 4 140 1 204 110 73 10 128 1 215 120 65 0 107 1 216 140 85 0 98 1 219 130 75 8 119 1 220 140 68 3 117 1 222 130 89 11 193 1 232 150 62 12 179 1 245 160 66 8 150 1 246 120 78 12 96 1 261 130 67 0 121 1 269 130 70 8 112 1 279 140 64 0 150 1 280 130 74

A study wants to look at the correlation between sugar consumption and the development of cavities.

The table below shows the average daily intake of sugar (g) and the total number of cavities per patient over the one-year study period.

Daily Sugar Intake / Number of Cavities

(X)                                    (Y)

30                                       2

40                                       3

150                                    3

90                                     0

75                                     1

25                                    1

110                                  4

4. What is the sample correlation coefficient given Σ(??−?̅)27?=1=12821.4, Σ(??−?̅)27?=1=12, and Σ(?−?̅)(?−?̅)=130? a. 0.33 b. 0.70 c. 0.87 d. -0.45

5. What type of correlation does this represent? a. Strong positive b. Strong inverse c. Weak positive d. Weak inverse

The investigator wants to construct a regression equation based on his current sample to be able to predict the number of cavities that a patient develops based only on their sugar intake given the standard deviation for the daily sugar intake is 43.25 and the standard deviation for the number of cavities is 1.41.

6. What is the slope of the line (i.e. what is b1)? a. 0.87 b. 0.01 c. 1.41 d. 0.50

7. What is the y-intercept (i.e. what is b0)? a. 1.26 b. 0.50 c. 0.01 d. 1.15

8. What is the predicted number of cavities for someone who consumes on average 45 grams of sugar a day? a. 1.71 b. 1.55 c. 0.67 d. 1.10

A study wants to look at the correlation between sugar consumption and the development of cavities. The table below shows the average daily intake of sugar (g) and the total number of cavities per patient over the one-year study period.

Daily Sugar Intake / Number of Cavities

(X)                                      (Y)         

30                                         2

40                                         3

150                                      3

90                                        0

75                                       1

25                                        1

110                                     4

4. What is the sample correlation coefficient given Σ(??−?̅)27?=1=12821.4, Σ(??−?̅)27?=1=12, and Σ(?−?̅)(?−?̅)=130?

a. 0.33 b. 0.70 c. 0.87 d. -0.45

5. What type of correlation does this represent?

a. Strong positive b. Strong inverse c. Weak positive d. Weak inverse

The investigator wants to construct a regression equation based on his current sample to be able to predict the number of cavities that a patient develops based only on their sugar intake given the standard deviation for the daily sugar intake is 43.25 and the standard deviation for the number of cavities is 1.41.

6. What is the slope of the line (i.e. what is b1)? a. 0.87 b. 0.01 c. 1.41   d. 0.50

7. What is the y-intercept (i.e. what is b0)? a. 1.26 b. 0.50 c. 0.01 d. 1.15

8. What is the predicted number of cavities for someone who consumes on average 45 grams of sugar a day?

Q1. ( 50 marks) please match word count to get a thumbs up

a. What is franchising? (150 words)

b. Analyze some industries in Dubai where franchising is expected to grow ( 220 word)

c. Why is pricing important for small businesses? ( 160 word)

Payroll Register

The following data for Throwback Industries Inc. relate to the payroll for the week ended December 9, 20Y8:

Employees Mantle and Williams are office staff, and all of the other employees are sales personnel. All sales personnel are paid 1½ times the regular rate for all hours in excess of 40 hours per week. The social security tax rate is 6%, and Medicare tax is 1.5% of each employee's annual earnings. The next payroll check to be used is No. 901.

Required:

1. Prepare a payroll register for Throwback Industries Inc. for the week ended December 9, 20Y8. Assume the normal working hours in a week are 40 hours. Enter amounts as positive numbers. Round your intermediate calculations and final answers to the nearest whole cent (two decimal places).

2. Journalize the entry to record the payroll for the week. If required, round your answers to two decimal places. If an amount box does not require an entry, leave it blank.

You are a human resources manager. Due to an economic down turn, you are required to terminate two employees. You are asked to consider two employees in order to determine what their pay in lieu of notice (severance package will be). On review of the files, you find the following information:

Employee #1 – Paul

•           Employed for 3 years

•           Current position is vice-president with 20 employees reporting to him

•           40 years of age

•           Has unique skills

Employee #2 – Mary

•           Employed for 30 years

•           Works as an administrative assistant

•           50 years of age

List two factors to consider in determining the severance package for each of Paul and Mary. Plus with respect to each employee indicate whether that factor will increase or decrease severance payable. ( Alberta, Canada)

A sample of 220 patients of a family medicine practice was surveyed two weeks after their doctor's visit to ask them whether the symptoms that prompted their visit improved, and whether they complied with the physician's treatment plan. The following table contains the results.

​

Is there a relationship between the two variables?

1. Debt Corporation is financed with 50 percent debt, while equity Corporation has the same amount of total assets, but is financed entirely with equity. Both Corporation have a marginal tax rate of 40 percent. Which of the following statements is most correct.

   1. If the two corporations have the same return on assets, Equity Corporation will have a higher return on equity.

   2. If the two corporations have the same basic earning power (BEP), Equity Corporation will have a higher return on assets.

   3. If the two corporations have the same level of sales and basic earning power, Equity Corporations will have a lower net profit margin.

   4. All of the answers above are correct.

   5. None of the answers above are correct.

Can you also explain why?

WG Investors is looking at three different investment opportunities. Investment one is a​ five-year investment with a cost of ​$400 and a promised payout of ​$800 at maturity. Investment two is a​ seven-year investment with a cost of ​$400 and a promised payout of ​$1,040. Investment three is a​ ten-year investment with a cost of ​$400 and a promised payout of ​$1,960. WG Investors can take on only one of the three investments. Assuming that all three investment opportunities have the same level of​ risk, calculate the effective annual return for each​ investment, and select the best investment choice.

What is the effective annual return for investment​ one, a​ five-year investment with a cost of ​$400 and a promised payout of $800 at​ maturity?

WG Investors is looking at three different investment opportunities. Investment one is a​ five-year investment with a cost of

​$260 and a promised payout of $520 at maturity. Investment two is a​ seven-year investment with a cost of ​$260 and a promised payout of

​$702. Investment three is a​ ten-year investment with a cost of ​$260 and a promised payout of ​$1,196.

WG Investors can take on only one of the three investments. Assuming that all three investment opportunities have the same level of​ risk, calculate the effective annual return for each​ investment, and select the best investment choice.

What is the effective annual return for investment​ one, a​ five-year investment with a cost of ​$260 and a promised payout of $520 at​ maturity?