Consider this situation. Julie is the owner of an airport shuttle. The shuttle transports passengers between Bowling Green and the Nashville Airport. Most customers pay with cash because there is a big discount. Since she is old and spends most of the time in Florida, she hired Mark, as the only employee and driver. Julie is far away from Bowling Green, therefore she has to believe Mark unless there is an unambiguously clear evidence against Mark’s claim/report. Assume that Mark is rational (in economics, rational is synonymous with selfish) and he will always cheat on Julie if doing so is beneficial (increasing his monetary benefits).

     Julie is considering the following five possible compensation methods:

            I)           Pay Mark a flat salary (e.g., $3,500 each month)

            II)         Pay Mark an amount equal to reported revenue less fixed amount

             (e.g., reported revenue less $3,000; negative pay if reported revenue < $3,000)

            III)       Pay Mark a certain percent of sales (e.g., 30% of reported fares from passengers)

4. Pay Mark on an hourly basis (e.g., $25 per hour * Reported work hours)
5. Pay Mark based on the mileage (e.g., $0.30 for each mile added in the mileage gauge)
6. Pay Mark based on his efforts (how hard he works)

Julie is trying to find the best method in avoiding potential cheating by Mark.

Required:

A. Which of the following methods is the best one as far as the owner Julie is concerned? And why?

B. For each of the other 5 methods (the ones you did not choose in A), explain why it is not good for Julie.

Instructions

1. Question: Is “age” in the Patients dataset (Excel) normally distributed? To answer this question, follow the directions in Chapter 6 (Comparing Data Characteristics to Theoretical Properties and Constructing the Normal Probability Plot). (15 points)
2. Assuming that the “age” variable for the individuals in the Patients dataset is normally distributed, what is the probability that the age of a patient in this dataset: (15 points)
   1. Is less than 45?
   2. Is greater than 55?
   3. Lies between 45 and 55?
3. When you have completed your assignment, save a copy for yourself and submit a copy to your instructor using the Assignment submission page by the end of the workshop. Showing your work is required, not just providing answers without showing how you arrived at them. Here is the age data from the Excel sheet:

The function print_mean() that you wrote in the previous lesson calculates an average value and prints it on the screen. Change this function so that instead of printing the average it returns the average.In order to calculate the sum, you won't need to form a loop; call the function column_sum() instead.

# columns are [0]title [1]year [2]rating [3]length(min) [4]genre [5]budget($mil) [6]box_office_gross($mil)
oscar_data = [
["The Shape of Water", 2017, 6.914, 123, ['sci-fi', 'drama'], 19.4, 195.243464],
["Moonlight", 2016, 6.151, 110, ['drama'], 1.5, 65.046687],
["Spotlight", 2015, 7.489, 129, ['drama', 'crime', 'history'], 20.0, 88.346473],
["Birdman", 2014, 7.604, 119, ['drama', 'comedy'], 18.0, 103.215094],
["12 Years a Slave", 2013, 7.71, 133, ['drama', 'biography', 'history'], 20.0, 178.371993],
["Argo", 2012, 7.517, 120, ['thriller', 'drama', 'biography'], 44.5, 232.324128],
["The Artist", 2011, 7.942, 96, ['drama', 'melodrama', 'comedy'], 15.0, 133.432856],
["The King\'s Speech", 2010, 7.977, 118, ['drama', 'biography', 'history'], 15.0, 414.211549],
["The Hurt Locker", 2008, 7.298, 126, ['thriller', 'drama', 'war', 'history'], 15.0, 49.230772],
["Slumdog Millionaire", 2008, 7.724, 120, ['drama', 'melodrama'], 15.0, 377.910544],
["No Country for Old Men", 2007, 7.726, 122, ['thriller', 'drama', 'crime'], 25.0, 171.627166],
["The Departed", 2006, 8.456, 151, ['thriller', 'drama', 'crime'], 90.0, 289.847354],
["Crash", 2004, 7.896, 108, ['thriller', 'drama', 'crime'], 6.5, 98.410061],
["Million Dollar Baby", 2004, 8.075, 132, ['drama', 'sport'], 30.0, 216.763646],
["The Lord of the Rings: Return of the King", 2003, 8.617, 201, ['fantasy', 'drama', 'adventure'], 94.0, 1119.110941],
["Chicago", 2002, 7.669, 113, ['musical', 'comedy', 'crime'], 45.0, 306.776732],
['A Beautiful Mind', 2001, 8.557, 135, ['drama', 'biography', 'melodrama'], 58.0, 313.542341],
["Gladiator", 2000, 8.585, 155, ['action', 'drama', 'adventure'], 103.0, 457.640427],
["American Beauty", 1999, 7.965, 122, ['drama'], 15.0, 356.296601],
["Shakespeare in Love", 1998, 7.452, 123, ['drama', 'melodrama', 'comedy', 'history'], 25.0, 289.317794],
["Titanic", 1997, 8.369, 194, ['drama', 'melodrama'], 200.0, 2185.372302],
["The English Patient", 1996, 7.849, 155, ['drama', 'melodrama', 'war'], 27.0, 231.976425],
["Braveheart", 1995, 8.283, 178, ['drama', 'war', 'biography', 'history'], 72.0, 210.409945],
["Forrest Gump", 1994, 8.915, 142, ['drama', 'melodrama'], 55.0, 677.386686],
["Schindler\'s List", 1993, 8.819, 195, ['drama', 'biography', 'history'], 22.0, 321.265768],
["Unforgiven", 1992, 7.858, 131, ['drama', 'western'], 14.4, 159.157447],
["Silence of the Lambs", 1990, 8.335, 114, ['thriller', 'crime', 'mystery', 'drama', 'horror'], 19.0, 272.742922],
["Dances with Wolves", 1990, 8.112, 181, ['drama', 'adventure', 'western'], 22.0, 424.208848],
["Driving Miss Daisy", 1989, 7.645, 99, ['drama'], 7.5, 145.793296],
["Rain Man", 1988, 8.25, 133, ['drama'], 25.0, 354.825435],
]

def column_sum(data, column):
result = 0
for row in data:
result += row[column]
return result

def column_mean(data, column):
# < write code here >
  

mean_score = column_mean(oscar_data, 2)
print('Average rating: {:.2f}'.format(mean_score))

mean_length = column_mean(oscar_data, 3)
print('Average length: {:.2f} min.'.format(mean_length))

mean_budget = column_mean(oscar_data, 5)
print('Average budget: ${:.2f} mil.'.format(mean_budget))

mean_gross = column_mean(oscar_data, 6)
print('Average revenue: ${:.2f} mil.'.format(mean_gross))

# columns are [0]title [1]year [2]rating [3]length(min) [4]genre [5]budget($mil) [6]box_office_gross($mil)
oscar_data = [
["The Shape of Water", 2017, 6.914, 123, ['sci-fi', 'drama'], 19.4, 195.243464],
["Moonlight", 2016, 6.151, 110, ['drama'], 1.5, 65.046687],
["Spotlight", 2015, 7.489, 129, ['drama', 'crime', 'history'], 20.0, 88.346473],
["Birdman", 2014, 7.604, 119, ['drama', 'comedy'], 18.0, 103.215094],
["12 Years a Slave", 2013, 7.71, 133, ['drama', 'biography', 'history'], 20.0, 178.371993],
["Argo", 2012, 7.517, 120, ['thriller', 'drama', 'biography'], 44.5, 232.324128],
["The Artist", 2011, 7.942, 96, ['drama', 'melodrama', 'comedy'], 15.0, 133.432856],
["The King\'s Speech", 2010, 7.977, 118, ['drama', 'biography', 'history'], 15.0, 414.211549],
["The Hurt Locker", 2008, 7.298, 126, ['thriller', 'drama', 'war', 'history'], 15.0, 49.230772],
["Slumdog Millionaire", 2008, 7.724, 120, ['drama', 'melodrama'], 15.0, 377.910544],
["No Country for Old Men", 2007, 7.726, 122, ['thriller', 'drama', 'crime'], 25.0, 171.627166],
["The Departed", 2006, 8.456, 151, ['thriller', 'drama', 'crime'], 90.0, 289.847354],
["Crash", 2004, 7.896, 108, ['thriller', 'drama', 'crime'], 6.5, 98.410061],
["Million Dollar Baby", 2004, 8.075, 132, ['drama', 'sport'], 30.0, 216.763646],
["The Lord of the Rings: Return of the King", 2003, 8.617, 201, ['fantasy', 'drama', 'adventure'], 94.0, 1119.110941],
["Chicago", 2002, 7.669, 113, ['musical', 'comedy', 'crime'], 45.0, 306.776732],
['A Beautiful Mind', 2001, 8.557, 135, ['drama', 'biography', 'melodrama'], 58.0, 313.542341],
["Gladiator", 2000, 8.585, 155, ['action', 'drama', 'adventure'], 103.0, 457.640427],
["American Beauty", 1999, 7.965, 122, ['drama'], 15.0, 356.296601],
["Shakespeare in Love", 1998, 7.452, 123, ['drama', 'melodrama', 'comedy', 'history'], 25.0, 289.317794],
["Titanic", 1997, 8.369, 194, ['drama', 'melodrama'], 200.0, 2185.372302],
["The English Patient", 1996, 7.849, 155, ['drama', 'melodrama', 'war'], 27.0, 231.976425],
["Braveheart", 1995, 8.283, 178, ['drama', 'war', 'biography', 'history'], 72.0, 210.409945],
["Forrest Gump", 1994, 8.915, 142, ['drama', 'melodrama'], 55.0, 677.386686],
["Schindler\'s List", 1993, 8.819, 195, ['drama', 'biography', 'history'], 22.0, 321.265768],
["Unforgiven", 1992, 7.858, 131, ['drama', 'western'], 14.4, 159.157447],
["Silence of the Lambs", 1990, 8.335, 114, ['thriller', 'crime', 'mystery', 'drama', 'horror'], 19.0, 272.742922],
["Dances with Wolves", 1990, 8.112, 181, ['drama', 'adventure', 'western'], 22.0, 424.208848],
["Driving Miss Daisy", 1989, 7.645, 99, ['drama'], 7.5, 145.793296],
["Rain Man", 1988, 8.25, 133, ['drama'], 25.0, 354.825435],
]

def column_sum(data, column):
result = 0
for row in data:
result += row[column]
return result

def column_mean(data, column):
total = column_sum(oscar_data, 6)
mean = total / len(data)
return mean

# < write code here >
  

mean_score = column_mean(oscar_data, 2)
print('Average rating: {:.2f}'.format(mean_score))

mean_length = column_mean(oscar_data, 3)
print('Average length: {:.2f} min.'.format(mean_length))

mean_budget = column_mean(oscar_data, 5)
print('Average budget: ${:.2f} mil.'.format(mean_budget))

mean_gross = column_mean(oscar_data, 6)
print('Average revenue: ${:.2f} mil.'.format(mean_gross))

An Empirical Approach to the Small Initial Trade Share Problem in General Equilibrium Models."Kuiper and van Tongeren (2006).
Write down Major findings and objective of the study?

In 2006 and early 2007, investment banks representing firms for sale saw financial buyers bidding more than strategic buyers. Why is this unusual and why was it happening?

Read Anderson, Narus, & van Rossum, (2006). In a 2-3 page assignment response, please include a high-level and general review of the concepts and content in the article.

The 2006 research paper by Paredez et al (full reference details below) provided direct evidence linking a role for microtubules in regulating cellulose microfibril deposition in the plant cell wall. Describe the major experimental findings reported in this paper and the significance of these findings to resolve long standing models that attempted to explain a role for cortical microtubules in controlling the direction of cellulose microfibril deposition. In explaining the experimental strategy used in this research, what was the rationale for using a CesA6 mutant line as part of their experimental approach?

Reference: Paredez, Somerville and Ehrhardt (2006) Visualization of cellulose synthase demonstrates functional association with microtubules. Science 312: 1491-1495.

The following excerpt is from the racial profiling data collection resource center In 2006, the New York City Police Department stopped a half-million pedestrians for suspected criminal involvement. Raw89 percent of the stops involved nonwhites. Do these statistics point to a racial bias in police officers' decisions to stop particular pedestrians? o they indicate that officers are particularly intrusive when stopping nonwhites?

Write a report that answers the questions posed using the fact thst 44% of New York City residents were classified as white in 2006. In your report, cite some shortcomings in using the proportion of white residents in the city to formulate likelihoods.

A property owner has provided you with the following information. Assume the owner has no other assets or liabilities. The annual gross revenue is $3,275,000. The debt service payment on the loan is $147,000 per month. The capitalization rate is 8%. Assets: Cash $ 1,000,000 Land 1,500,000 Building 29,500,000 Total Assets $ 32,000,000 Liabilities & Equity: Nonrecourse Liabilities $ 25,000,000 Partner’s Capital 7,000,000 Total Liabilities & Capital $ 32,000,000

14. What is the property’s NOI?

Calculate the Debt Service Coverage Ratio?

What is the Debt to Asset Ratio?

Last year’s Debt Ratio for the property was 74%. The industry average Debt to Asset ratio is 82%. Based on the available information would you consider this to be a low, normal or high risk investment and why?

What is the Effective Gross Income Multiplier?