Open Air_Traffic data. SETUP: It is believed that in July, as years go by we see higher and higher traffic. Given the data your job is to confirm or disprove this assertion.

4. What test/procedure did you perform? (4 points)

• a. Regression
• b. Two sided t-test
• c. One sided t-test
• d. Confidence Interval

5. What is the statistical interpretation? (4 points)

• a. Average of data is inconsistent with the claim
• b. P-value is too large to have a conclusive answer
• c. P-value is smaller than 5% thus we are confident to say that the slope is not zero.
• d. P-value is smaller than 5% thus we are confident that the averages are different.
• e. None of these

6. What is the conclusion? (4 points)

• a. We cannot claim that in July, as years go by we see higher and higher traffic.
• b. We can claim that in July, as years go by we see higher and higher traffic.
• c. None of these

From 1997-2006, the returns on Magni were as follows, Using Blume's Formula:

A. What would be the 1-year average forecast?

B. What would be the 2-year average forecast?

C. What would be the 6-year average forecast?

D. What would be the 10-year average forecast?

Death Causes

1. Fill-in the tables below with the following information for each of the age groups:

• Number of deaths from all causes
• Number of deaths from accidents (unintentional injuries)
• Cause-specific death rate for accidents (unintentional injuries)

Calculate the age-specific all cause death rates for each group and the proportionate mortality ratio (PMR) for accidents (unintentional injuries).

TABLE A

TABLE B

1. Comment on the differences you observe across age groups among the different measures of mortality (keep the ratios in mind) in Table B.

2. Calculate and interpret the all-cause mortality rate for 2006.

3. What do the measures in Table B tell you about the risk of death from accidents (unintentional injuries) in each age group?

4. Explain why each measure of mortality in Table B is or is not a good indicator of risk.

5. Assuming the following information is accurate, calculate the case-fatality rate for accidents in 2006.

1. Use the data below to find the linear regression equation that best represents the given data and predict the revenue in 2013 (Copy data to Excel)

2. Then create Two new columns that represent the predication y =mx+b for each year and percent of growth for each year = (Revenue/Predication)*100

3. Use Excel to graph the linear model (x-axis years, y-axis revenue) and the linear equation of best fit.

1. Fill out the missing entry for prediction and percent of growth
2. Find the value of the linear correlation coefficient r.
3. Find the equation of the regression line, letting Number of years be the independent (x) variable.
4. Find the coefficient of determination.
5. Find the standard error of estimate s_e.

Compare the height, weight (in inches), and age for Eagles versus Patriots, using t tests. Provide the conclusions based on the t tests.

Eagles

Pats

You are the account manager in charge of Internet advertising at Impact Sales. Spending on Internet advertising has increased steadily over the last few years and you predict the growth will continue.

) Do you think a linear model is appropriate for this data? Explain clearly.

f) Find a quadratic model for this data since 2000.

g) Which model better fits your data? Support your answer with a scatter plot of the data and both models on the same set of axis.

h) Using the quadratic model what is the average rate of change between 2002 and 2004?

i) As the account manager what would you budget for Internet advertising in 2008?

TABLE:

Year Internet Advertising Spending (Billions)

2001 0

2002 0.3

2003 0.8

2004 1.9

2005 3

2006 4.3

2007 5.8

Hallstead Jewelers; Income Statements for Years Ended January 31 (thousands of dollars) 2003 2004 2006 Sales $8,583 $8,102 $10,711 Cost of goods sold 4,326 4,132 5,570 Gross margin $4,257 $3,970 $ 5,141 Expenses Selling expense Salaries 2,021 2,081 3,215 Commissions 429 405 536 Advertising 254 250 257 Administrative expenses 418 425 435 Rent 420 420 840 Depreciation 84 84 142 Miscellaneous expenses 53 93 122 Total expenses $3,679 $3,758 $ 5,547 Net income $ 578 $ 212 $ (406)

1. Exhibit 1 shows the Income Statements for the years ending January 31^st, 2003, 2004 and 2006 using absorption costing. Generate Income Statements using Variable Costing. Assume that cost of goods sold and commissions are variable.

Consider the data in the following table:

Use the above information to answer the following questions. Round your answers to four decimal places (i.e. 0.0105).

1. Estimate the average return for stock A.

2. Estimate the average return for stock B.

3. Estimate the volatility of stock A.

4.Estimate the volatility of stock B.

5 .Estimate the correlation between the two stocks.

Use the following information to answer the next two questions:

On January 2, 2004, Shady Corp. acquired equipment for $110,000. The estimated life of the equipment is 5 years, the estimated residual value is $10,000 and Shady Corp. uses the straight-line method for computing depreciation expense. On June 30^th of 2006 (2 and ½ years after acquiring the asset), Shady Corp sold the equipment for $50,000.

What two journals entries were made on June 30^th, 2006, on the date the asset was sold? directly below.

1. The first (adjusting) entry recorded on June 30th, 2006 was:

Provide answer towards the bottom of the answer sheet

2. The second entry to record the equipment sale on June 30th, 2006 was:

            Provide answer towards the bottom of the answer sheet

3. Find the correlation and regression lines for the data above.

r=

LinReg(ax+b)=