In a certain county, the sizes of family farms approximately follow mound-shaped (normal) distribution with a mean of 472 acres and a standard deviation of 27 acres.

(a) According to the empirical rule, approximately __% of family farms have a size between 418 and 526 acres.

(b) According to the empirical rule, approximately __% of family farms have a size between 391 and 553 acres.

(c) According to the empirical rule, approximately __% of family farms have a size between 445 and 499 acres.

For homes in a certain state, electric consumption amounts last year approximately followed a mound-shaped (normal) distribution with a mean of 1034 kilowatt-hours and a standard deviation of 182 kilowatt-hours.

(a) According to the empirical rule, approximately 99.7% of values in the distribution will be between these two bounds:
Lower-bound =___ kilowatt-hours and upper-bound = ___ kilowatt-hours.

(b) According to the empirical rule, approximately 68% of values in the distribution will be between these two bounds:
Lower-bound = ___ kilowatt-hours and upper-bound = ___ kilowatt-hours.

(c) According to the empirical rule, approximately 95% of values in the distribution will be between these two bounds:
Lower-bound = ___ kilowatt-hours and upper-bound = ___kilowatt-hours.

Aminah wish to perform the hypothesis testing H0: μ =1 versus H1: μ <1 versus with α=0.10. . The sample size 25 was obtained independently from a population with standard deviation 10. State the distribution of the sample mean given that null hypothesis is true and find the critical value, then calculate the values of sample mean if she reject the null hypothesis. Finally, compute the p-value, if the sample mean is -2.

The Russell 1000 is a stock market index consisting of the largest U.S. companies. The Dow Jones industrial Average is based on 30 large companies. The data giving the annual percentage returns for each of these stock indexes for 25 years are contained in the Excel Online file below. Construct a spreadsheet to answer the following questions.

a. Which of the following scatter diagrams accurately represents the data set?

_________Scatter diagram #1Scatter diagram #2Scatter diagram #3Scatter diagram #4

b. Compute the sample mean and standard deviation for each index (to 2 decimals).

c. Compute the sample correlation coefficient for these data (to 3 decimals).

d. Discuss similarities and differences in these two indexes.

_________There is a strong positive linear association between DJIA and Russell 1000There is a moderate positive linear association between DJIA and Russell 1000There is neither a positive nor a negative linear association between DJIA and Russell 1000There is a moderate negative linear association between DJIA and Russell 1000There is a strong negative linear association between DJIA and Russell 1000

The variance of the Russell 1000 is slightly _________largersmaller than that of the DJIA.

a. Which of the following scatter diagrams accurately represents the data set?

_________Scatter diagram #1Scatter diagram #2Scatter diagram #3Scatter diagram #4

b. Compute the sample mean and standard deviation for each index (to 2 decimals).

c. Compute the sample correlation coefficient for these data (to 3 decimals).

d. Discuss similarities and differences in these two indexes.

_________There is a strong positive linear association between DJIA and Russell 1000There is a moderate positive linear association between DJIA and Russell 1000There is neither a positive nor a negative linear association between DJIA and Russell 1000There is a moderate negative linear association between DJIA and Russell 1000There is a strong negative linear association between DJIA and Russell 1000

The variance of the Russell 1000 is slightly _________largersmaller than that of the DJIA.

You believe that there is a difference in salaries between genders in your industry. You know that the average salary for males is $100,000 per year, but you cannot find any information on female salaries. Thus, you collect data on female salaries to test your belief. For your study, what would be your null hypothesis?

A. µ < 100,000

B. µ = 100,000

C. µ ≤ 100,000

D. not enough information

This problem is from 2008.

The US Open is an annual two week tennis event in Flushing NY in late August, early September.

In a year with no significant rain interruption, the US Open makes approximately $275 million in revenue and incurs expenses of approximately $225 million, for a profit of $50 million. Of the $275 million in revenue approximately $100 million is from ticket sales. As a non-profit organization, it incurs no tax.

The US Open can work around rain delays but if all play is suspended in either the afternoon or evening sessions, tickets are good for the same session in the following year, in which case the USTA foregoes revenue. The largest ticket prices are for the women’s and men’s finals so a rain-out on either of these days forgoes the most revenue.

The Open is interested in buying a contract to protect itself from foregone revenues from rain interruptions during the finals. Working with its insurance broker, it approaches the insurance market to see if it can buy a weather derivative or insurance policy.

The US Open estimates that between foregone ticket sales and lost margin on concessions and broadcasting rights, a rain out on either the men’s or women’s finals will mean $30 mil in lost profits.

The insurance broker is able to secure an insurance policy that will indemnify the US Open if rainfall occurs during the men’s or women’s finals. The policy treats each event separately, meaning there is coverage and a corresponding premium charged for postponement of either final. The insurer is willing to provide a policy covering each separate event that will indemnify the US Open with a limit of $30 million and a policy premium of $10 million for each. As with all insurance policies, the US Open can collect the insurance payments only once it demonstrates the losses.

The weather desks at three major reinsurance holding companies with broker/dealers supply the probabilities associated with significant rainfall (> ¼ inch) on days 13 and 14 of this calendar year, which is 20% for either day, and conditional on rain on the 13th day, the chance of rain on the 14th day is 30%.

Write out all possible rain/dry possibilities for the 13th and 14th days, with their associated probabilities.

Without insurance, what are the profits if there are rain postponements to either or both finals?

Without insurance, what are the expected profits?

With insurance, what are profits if there are rain postponements?

With insurance what are profits if there is no rain?

What are the expected profits if insurance is purchased?

Should the US Open explore including additional days into the policy?

Over a ten year period, assuming baseline revenue and costs are approximately the same amounts as today, what would the US Open expect to earn (i) in the absence of an insurance policy and (ii) with the insurance policy?

The weather desk is also willing to write two weather derivative contracts, one for day 13 and one for day 14, each with a payout of $30 million and a cost of $12 million. The derivative pays the US Open regardless of whether play is suspended or not. It pays based on measured rainfall within 24 hour period exceeding ¼ of an inch.

What is the best strategy for the US Open to manage its exposure to rain?

Explain.

Without insurance, what are the profits if there are rain postponements to either or both finals?

Without insurance, what are Expected profits?

With insurance, what are profits if there are rain postponements?

With insurance what are profits if there is no rain?

Should the US Open explore including additional days into the policy?

Over a ten year period, assuming baseline revenue and costs are approximately the same amounts as today, what would the US Open expect to earn (i) in the absence of an insurance policy and (ii) with the insurance policy?

What is the best strategy for the US Open to manage its exposure to rain?

This problem is from 2008.

The US Open is an annual two week tennis event in Flushing NY in late August, early September.

In a year with no significant rain interruption, the US Open makes approximately $275 million in revenue and incurs expenses of approximately $225 million, for a profit of $50 million. Of the $275 million in revenue approximately $100 million is from ticket sales. As a non-profit organization, it incurs no tax.

The US Open can work around rain delays but if all play is suspended in either the afternoon or evening sessions, tickets are good for the same session in the following year, in which case the USTA foregoes revenue. The largest ticket prices are for the women’s and men’s finals so a rain-out on either of these days forgoes the most revenue.

The Open is interested in buying a contract to protect itself from foregone revenues from rain interruptions during the finals. Working with its insurance broker, it approaches the insurance market to see if it can buy a weather derivative or insurance policy.

The US Open estimates that between foregone ticket sales and lost margin on concessions and broadcasting rights, a rain out on either the men’s or women’s finals will mean $30 mil in lost profits.

The insurance broker is able to secure an insurance policy that will indemnify the US Open if rainfall occurs during the men’s or women’s finals. The policy treats each event separately, meaning there is coverage and a corresponding premium charged for postponement of either final. The insurer is willing to provide a policy covering each separate event that will indemnify the US Open with a limit of $30 million and a policy premium of $10 million for each. As with all insurance policies, the US Open can collect the insurance payments only once it demonstrates the losses.

The weather desks at three major reinsurance holding companies with broker/dealers supply the probabilities associated with significant rainfall (> ¼ inch) on days 13 and 14 of this calendar year, which is 20% for either day, and conditional on rain on the 13^th day, the chance of rain on the 14^th day is 30%.

1. Write out all possible rain/dry possibilities for the 13^th and 14^th days, with their associated probabilities.
2. Without insurance, what are the profits if there are rain postponements to either or both finals?
3. Without insurance, what are the expected profits?
4. With insurance, what are profits if there are rain postponements?
5. With insurance what are profits if there is no rain?
6. What are the expected profits if insurance is purchased?
7. Should the US Open explore including additional days into the policy?
8. Over a ten year period, assuming baseline revenue and costs are approximately the same amounts as today, what would the US Open expect to earn (i) in the absence of an insurance policy and (ii) with the insurance policy?

The weather desk is also willing to write two weather derivative contracts, one for day 13 and one for day 14, each with a payout of $30 million and a cost of $12 million. The derivative pays the US Open regardless of whether play is suspended or not. It pays based on measured rainfall within 24 hour period exceeding ¼ of an inch.

1. What is the best strategy for the US Open to manage its exposure to rain?

Explain.

1. Without insurance, what are the profits if there are rain postponements to either or both finals?
2. Without insurance, what are Expected profits?

3. With insurance, what are profits if there are rain postponements?
4. With insurance what are profits if there is no rain?

5. Should the US Open explore including additional days into the policy?

6. Over a ten year period, assuming baseline revenue and costs are approximately the same amounts as today, what would the US Open expect to earn (i) in the absence of an insurance policy and (ii) with the insurance policy?
7. What is the best strategy for the US Open to manage its exposure to rain?

please make sure the second part is answer.  

Two hospital emergency rooms use different procedures for triage of their patients. A local health care provider conducted a study to determine if there is a significant difference in the mean waiting time of patients for both hospitals. The 40 randomly selected subjects from Medina General Hospital (population 1) produce a mean waiting time of 18.3 minutes and a standard deviation of 2.1 minutes. The 50 randomly selected patients from Southwest General Hospital (population 2) produce a mean waiting time of 19.2 minutes and a standard deviation of 2.92 minutes. Using a significance level of α = .02, the critical value(s) for rejecting the null hypothesis is(are) -2.33 ±1.988 +2.33 -2.37 ±2.33 +2.37 ±2.37 +1.988 -1.988

Research a major (note the word major) security/ privacy breach that occurred in the healthcare or public health domain in the last 5 years. Answer the following questions.

1. What was the impact on patients?
2. What could have been done to prevent it?
3. What was the penalty / fine awarded to the healthcare organization?

Nine owners of Honda Civics in Richmond want to know if they get different gas mileage with their cars than what the Honda Corporation reports. Honda of America states that all Honda Civics sold in America get an average of 33 MPG (miles per gallon). The nine Honda owners drive their cars and record the MPG listed below. Use a single-sample t-test to determine the outcome (alpha = .05, two-tailed).

Owner 1: 29 MPG
Owner 2: 32 MPG
Owner 3: 31 MPG
Owner 4: 30 MPG
Owner 5: 30 MPG
Owner 6: 29 MPG
Owner 7: 28 MPG
Owner 8: 31 MPG
Owner 9: 30 MPG
M = 30

In the box below, provide the following information:
Null Hypothesis in sentence form (1 point):
Alternative Hypothesis in sentence form (1 point):
Critical Value(s) (2 points):
Calculations WITH COHEN'S D (4 points): Note: the more detail you provide, the more partial credit that I can give you if you make a mistake.
Outcome (determination of significance or not, and what this reflects in everyday language, 2 points)

Please discuss the purpose of hypothesis testing. In your response, provide an example of a null hypothesis and alternative hypothesis. Why is hypothesis testing important for researchers?

3) President Trump’s approval rating is 42%. Suppose that 10 people were chosen at random

a) Find the probability that 5 of the 10 people approve of the job President Trump is doing.

b) Find the probability that at most 3 of the 10 people approve of the job President Trump is doing.

c) Find the probability that at least 3 of 10 people approve of the job President Trump is doing.

Please use an example to discuss the Analysis of Variance. Please discuss why some experts believe it should be called “Analysis of Means.”

Please discuss the advantages and disadvantages of using surveys to collect data from subjects. Why does the response rate to surveys matter? In your discussion, please elaborate on a survey you have completed in the past. Why did you elect to participate?

Let p be the (unknown) proportion of males in a town of 100, 000 residents. A political scientist takes a simple random sample of 100 residents from this town.

(a) Write down the exact pmf, as well as an approximate pmf, for the number of males in the sample. (They should both depend on p).

(b) If the number of males in the sample is 55 or more, the political scientist will claim that there are more males than females in the town. If the number of males in the sample is less than 55, he/she will claim that the number of males in the town is smaller or equal to that of females. What is approximately the probability that his/her claim will be correct if the true proportion of males in the town, p, is 50%? What if p = 55%?

(c) Report an approximate 68% confidence interval for p if 65 of the 100 residents in the sample are male.