Audience Analysis due 2/20/2017 at 10am Eastern Time
BUGN 280 Excel Project Data File Information
1 – Airline Arrival Study
Direct memos and reports to Chief Operating Officer (COO) of United Airlines
A random sample of 444 flights from LAX to JFK in one year. The flight distance is 2475 miles.
Numerical Variable of Interest:
ArrDelay = arrival delay in minutes
where “-“ values are early arrivals (in minutes), “0” values are “on time” arrivals and “+” values are late arrivals (in minutes).
Numerical Predictor Variable:
DepDelay = departure delay in minutes
Categorical Breakdown Variable:
Carrier = airline used
where “1” = American Airlines , “0”= United Airlines
Categorical Variable of Interest:
Time = time of departure (A.M., P.M.)
2 – Albuquerque NM RE Study
Direct memos and reports to Chief Operating Officer (COO) of Weichert Realtors, New Mexico
A random sample of 117 homes for resale in Albuquerque, NM.
Numerical Variable of Interest:
Price = price of home in thousands of dollars (k)
Numerical Predictor Variable:
Sqft = square footage of dwelling
Categorical Breakdown Variable:
Custom = custom design
where “1” = Yes, “0” = No
Categorical Variable of Interest:
Corner = house on corner lot (Yes, No)
3 – American Community Survey
Direct memos and reports to the Editor, Business Section, The New York Times.
A random sample of 266 responses to the American Community Survey.
Numerical Variable of Interest:
WorkInc = work income in thousands of dollars (k)
Numerical Predictor Variable:
HrsWorked = hours worked per week
Categorical Breakdown Variable:
Gender = gender of respondent
where “1” = Male , “0”= Female
Categorical Variable of Interest:
HowComm = most typical method of commuting to work (bus, car, subway/rail, taxi, other, works at
home, not applicable)
4 – Automobile Study
Direct memos and reports to Chief Operating Officer (COO) of the American Automobile Association (AAA)
Automobile features taken from a sample of 171 car models.
Numerical Variable of Interest:
MPG = miles per gallon
Numerical Predictor Variable:
Weight = weight of automobile in pounds
Categorical Breakdown Variable:
Origin = origin of car
where “1” = US, “0” = Asia or Europe
Categorical Variable of Interest:
TypeAuto = type of automobile (4 door hatchback, 4 door SUV, coupe, minivan, sedan, wagon)
5 – Beer Study
Direct memos and reports to the Editor, Consumer Reports
A study of features in a random sample of 139 beers.
Numerical Variable of Interest:
PctAlcohol = percent alcohol content in the beer
Numerical Predictor Variable:
Calories = calories in the beer
Categorical Breakdown Variable:
DistType = distribution type- where “1” = National , “0”= Regional
Categorical Variable of Interest:
Light = whether the beer product is considered “light” (yes, no)
6 – Birth Weight Study in MA
Direct memos and reports to Commissioner of Health, Commonwealth of Massachusetts
A random sample of 189 mothers were studied with respect to the birth weight of their child.
Numerical Variable of Interest:
BWT = birth weight in grams (below 2500 is considered low)
Numerical Predictor Variable:
WEIGHT = weight (in pounds) of mother at last menstrual period
Categorical Breakdown Variable:
Smoke = smoking during pregnancy
where “1” = Yes, “0” = No
Categorical Variable of Interest:
Race = race of mother (white, black, other)
7 – Birth Weight Study in NC
Direct memos and reports to Commissioner of Health, State of North Carolina
A random sample of 1000 births from the state of North Carolina.
Numerical Variable of Interest:
BirthWt = birth weight of child in pounds
Numerical Predictor Variable:
Weeks = weeks of gestation
Categorical Breakdown Variable:
MSmoke = was the mother smoking during pregnancy
where “1” = Yes, “0”= No
Categorical Variable of Interest:
MRace = mother’s race (white, non-white)
8 – Bond Funds Study
Direct memos and reports to Chief Financial Officer (CFO) of Vanguard
A random sample of 180 bond funds and their characteristics.
Numerical Variable of Interest:
Five-Year Return = five-year return on investment (in percent)
Numerical Predictor Variable:
One-Year Return = one-year return on investment (in percent)
Categorical Breakdown Variable:
Category = category of fund
where “1” = intermediate government “0” = short term corporate
Categorical Variable of Interest:
Risk = risk of fund (above average, average, below average)
9 – Business Valuation Study
Direct memos and reports to CFO, Pfizer Corporation
Financial information pertaining to a random sample of 71 companies in the pharmaceutical industry.
Numerical Variable of Interest:
Return on Equity = ROE (in %).
Numerical Predictor Variable:
Price/Book Value = price to book value ratio.
Categorical Breakdown Variable:
Type = type of company: PharmPrep (pharmacy prep products) or BioProducts (biological products)
Categorical Variable of Interest:
Debt/EBITDA Ratio = ratio value: Low (Below 4), Moderate/High (4 or Above)
10 – Candidate Assessment Study
Direct memos and reports to President Susan Cole, Montclair State University
A random sample of 120 faculty assessments of job candidate qualifications.
Numerical Variable of Interest:
Salary = salary in k offered to job candidate.
Numerical Predictor Variable:
Competency Rating = a 7-point numerical scale where 1 is “low” and 7 is “high”
Categorical Breakdown Variable:
Gender-Candidate = gender of job candidate
where M = Male, F = Female
Categorical Variable of Interest:
School = type of education institution: Private or Public
11 – Cereal Study
Direct memos and reports to Chief Operating Officer (COO) of General Mills
A study of a random sample of 76 cold cereal characteristics.
Numerical Variable of Interest:
calories = calories per serving
Numerical Predictor Variable:
weight = weight in ounces of one serving
Categorical Breakdown Variable:
Mfr= manufacturer of cereal product
where “1” = General Mills or Kelloggs , “0”= Other
Categorical Variable of Interest:
Cups = cups in a serving (one or more, less than one)
12 – College Football Study
Direct memos and reports to Provost Willard Gingerich, Montclair State University
A random sample of financial information regarding 105 college football teams.
Numerical Variable of Interest:
Football Net Revenue = net revenue in $ obtained by football program.
Numerical Predictor Variable:
Total Pay = total pay in $ to the coach of the football team.
Categorical Breakdown Variable:
Location = location of the college with respect to east or west of the Mississippi River
where E = East, W = West
Categorical Variable of Interest:
Conference = institutional conference affiliation:
(ACC, Big East, Big Ten, Big 12, CUSA, Ind., MAC, Mt. West, PAC-12, SEC, Sun Belt, WAC
13 – Community College Study
Direct memos and reports to the President, Berry County Community College
A survey for a random sample of 562 community college students at a large institution.
Numerical Variable of Interest:
Working = hours of work per week
Numerical Predictor Variable:
Credit hrs = number of credits enrolled
Categorical Breakdown Variable:
Handed = hand mainly or always used for writing
where “1” = right-handed, “0” = left-handed
Categorical Variable of Interest:
Gender = gender of student (Male, Female)
14 – Commuting Study
Direct memos and reports to Commissioner of Transportation, City of Atlanta
A random sample of 1000 commuters’ characteristics, 500 from Atlanta and 500 from St. Louis.
Numerical Variable of Interest:
Time = commuting time in minutes
Numerical Predictor Variable:
Distance = commuting distance in miles
Categorical Breakdown Variable:
City = city of respondent
where “1” = Atlanta , “0”= St. Louis
Categorical Variable of Interest:
Gender = gender of respondent (m, f)
15 – Credit Unions Study
Direct memos and reports to Editor, Business Section, The New York Times
A random sample of 1179 credit unions with assets less than 10 million dollars and their characteristics.
Numerical Variable of Interest:
Total Net Worth = total net worth in millions of dollars
Numerical Predictor Variable:
Total Investment = total investment in millions of dollars
Categorical Breakdown Variable:
AssetSize = asset size
where “1” = 5 to 10 billion $ (i.e., “larger”), “0” = under 5 billion $ (i.e., “smaller”)
Categorical Variable of Interest:
Region = region of the country (R1, R2, R3, R4, R5)
16 – Employee Survey
Direct memos and reports to Secretary, United States Department of Labor
A random sample of 400 employee characteristics.
Numerical Variable of Interest:
Salary = salary in thousands of dollars (k)
Numerical Predictor Variable:
WorkHrs = hours worked last week
Categorical Breakdown Variable:
BudgetDec = is the employee involved in budgetary decisions
where “1” = Yes , “0”= No
Categorical Variable of Interest:
Gender = gender of employee (male, female)
17 – Faculty Evaluations in TX Study
Direct memos and reports to Commissioner of Higher Education, the State of Texas
A random sample of 182 faculty members’ evaluations conducted by students at Texas universities.
Numerical Variable of Interest:
fac_eval = faculty evaluation (where 1 = poor through 5 = excellent)
Numerical Predictor Variable:
course_eval = course evaluation (where 1 = poor through 5 = excellent)
Categorical Breakdown Variable:
School = university faculty member is teaching at
where “1” = Texas Austin, “0” = Other
Categorical Variable of Interest:
Rank = rank of faculty member (tenured, not-tenured)
18 – GSS Study
Direct memos and reports to Secretary, United States Department of Labor
GSS survey displaying a random sample of 904 individuals.
Numerical Variable of Interest:
SEI = Social Economic Index of individual
Numerical Predictor Variable:
PRESTIGE = Occupational Prestige Score (where 0 = NA)
Categorical Breakdown Variable:
Race = race of individual responding
where “1” = White, “0”= Non-White
Categorical Variable of Interest:
Gender = gender of individual responding (Male, Female)
19 – Heart Stent Study
Direct memos and reports to President, American Heart Association
A random sample of 100 coronary heart disease patients who had stents inserted.
Numerical Variable of Interest:
total_labor_cost = labor cost in dollars
Numerical Predictor Variable:
total_device_cost = cost of device in dollars
Categorical Breakdown Variable:
Outcome = outcome of stent insert procedure
where “1” = Successful, “0” = No Change or Failure
Categorical Variable of Interest:
Gender = gender of patient (M, F)
20 – Human Resources Survey
Direct memos and reports to Vice President for Human Resources, The MLB Corporation
The data are a random sample of 120 employee responses to a survey conducted by the VP of Human Resources at a large company.
Numerical Variable of Interest:
Salary = salary of the employee in thousands of dollars
Numerical Predictor Variable:
Age = age in years
Categorical Breakdown Variable:
Ethnicity = ethnicity of the employee
where “1” = Minority , “0”= Not Minority
Categorical Variable of Interest:
Gender = gender of employee (Male, Female)
21 – LI RE Study
Direct memos and reports to Chief Operating Officer (COO) of Weichert Realtors, Long Island, NY
A random sample of 90 home characteristics in three Long Island communities.
Numerical Variable of Interest:
AppraisedValue = appraised values of homes in thousands of dollars (k)
Numerical Predictor Variable:
House Size = size of dwelling in square feet
Categorical Breakdown Variable:
Town = Long Island community
where “1” = Freeport, “0” = Glen Cove or Roslyn
Categorical Variable of Interest:
Pool = whether the property has a pool (Yes, No)
22 – Loans & Debt Study
Direct memos and reports to Editor, Business Section, The New York Times.
Loans and credit card debt study from a random sample of 260 college students.
Numerical Variable of Interest:
Loans = loans in $ outstanding
Numerical Predictor Variable:
CC Debt = credit card debt in dollars outstanding
Categorical Breakdown Variable:
Gender = gender of respondent
where “1” = Male , “0”= Female
Categorical Variable of Interest:
Class = class level of registered student (fr, so, jr, sr)
23 – Montclair & Millburn RE Study
Direct memos and reports to Chief Operating Officer (COO) of Weichert Realtors, New Jersey
A random sample of 93 homes sold in Montclair and Millburn New Jersey.
Numerical Variable of Interest:
PRICE = price in thousands of dollars (k) of the house sold
Numerical Predictor Variable:
ASSESSVAL == assessed value of house in thousands of dollars (k)
Categorical Breakdown Variable:
TOWN = location of house sold
where “1” = Montclair, “0”= Millburn
Categorical Variable of Interest:
STYLE = style of house (bi-level, Cape Cod, colonial, custom home, ranch, split level, Tudor, Victorian )
24 – Mutual Funds Study
Direct memos and reports to Editor, Business Section, The New York Times.
A random sample of 868 mutual funds and their characteristics.
Numerical Variable of Interest:
Five-Year Return = five-year mutual fund return (in percent)
Numerical Predictor Variable:
Three-Year Return = three-year mutual fund return (in percent)
Categorical Breakdown Variable:
Objective = objective of mutual fund
where “1” = Growth, “0” = Value
Categorical Variable of Interest:
Fees = managerial fees (Yes, No)
25 – Nutrition Study
Direct memos and reports to Commissioner of Health, State of New York.
A random sample of 315 patients involved in a nutrition study.
Numerical Variable of Interest:
Calories = amount of calories consumed per day
Numerical Predictor Variable:
Fat = amount of fat consumed per day
Categorical Breakdown Variable:
Smoke = does the patient smoke
where “1” = Yes, “0”= No
Categorical Variable of Interest:
Gender = gender of patient (Male, Female)
26 – PA RE Study
Direct memos and reports to Chief Operating Officer (COO) of Weichert Realtors, Pennsylvania
Assessed value and characteristics of a sample of 362 recently built homes in PA.
Numerical Variable of Interest:
AssessedValue = assessed value in thousands of dollars (k)
Numerical Predictor Variable:
TotalRooms = total number of rooms in the house
Categorical Breakdown Variable:
Basement= does the house have a basement
where “1” = Yes , “0”= No
Categorical Variable of Interest:
Fireplace = does the house have a fireplace (absent, present)
27 – Public College Value Study
Direct memos and reports to Secretary, United States Department of Education
A random sample of 100 public colleges and universities and their characteristics.
Numerical Variable of Interest:
4-Yr.Grad.Rate = four year graduation rate (in percent)
Numerical Predictor Variable:
Total cost per yr (in state) = total cost in dollars per student per year at institution
Categorical Breakdown Variable:
Region = location of college or university
where “1” = Atlantic or Eastern “0” = Other
Categorical Variable of Interest:
DebtAbove20k = is average student debt at graduation above $20,000 (Y, N)
28 – Retirement Funds Study
Direct memos and reports to Professor Deniz Ozenbas, Montclair State University
A random sample of financial information regarding 316 mutual funds.
Numerical Variable of Interest:
3YrReturn% = return on investment (in %) over a three year period.
Numerical Predictor Variable:
1YrReturn% = return on investment (in %) over a one year period.
Categorical Breakdown Variable:
Type = type of fund: Growth or Value
Categorical Variable of Interest:
Risk = risk level for fund: Low, Average, High
29 – ROI College & University Study
Direct memos and reports to Secretary, United States Department of Education
Return on investment (ROI) data for a sample of 252 colleges and universities in the USA.
Numerical Variable of Interest:
30 YEAR NET ROI = 30 year net return on investment in dollars
Numerical Predictor Variable:
AVG AID AMOUNT = average amount of aid per student in dollars
Categorical Breakdown Variable:
TYPE = type of institution
where “1” = Private, “0” = Public
Categorical Variable of Interest:
CATEGORY = category of institution (public, private, private research, liberal arts, business, engineering,
art-music-design)
30 – TV Set Study
Direct memos and reports to Editor, Consumer Reports
A random sample of 174 Tv models with their characteristics.
Numerical Variable of Interest:
Overall Score = score provided by consumers rating the product.
Numerical Predictor Variable:
Quality Rating = summation of ratings of features provided by Consumer Reports.
Categorical Breakdown Variable:
Type TV = type of television
where P = Plasma, L = Liquid
Categorical Variable of Interest:
SizeGP = size of TV screen
Where Small = below 40”, Medium = 40” to 49”, Large = 50” or more
31 Urban Study
Direct memos and reports to Editor, Real Estate Section , The New York Times
A random sample of 198 urban resident characteristics.
Numerical Variable of Interest:
Internet Hrs = hours spent last week on the internet
Numerical Predictor Variable:
Hours worked = hours worked for pay last week
Categorical Breakdown Variable:
Gender = gender of urban resident
where “1” = Male, “0” = Female
Categorical Variable of Interest:
Political Philo = political philosophy of the urban resident (Liberal, Moderate, Conservative)
32 – Used Autos Study
Direct memos and reports to Chief Operating Officer (COO) of the American Automobile Association (AAA)
A random sample of 743 recently sold used cars and their characteristics.
Numerical Variable of Interest:
Price = price in thousands of dollars (k)
Numerical Predictor Variable:
Mileage = mileage at sale of used vehicle
Categorical Breakdown Variable:
Origin = origin of vehicle
where “1” = USA , “0”= Asia or Europe
Categorical Variable of Interest:
Type = type of vehicle (Coupe, Minivan Muscle Cr, PickupT, Sedan, SedanWg, Sports Cr, SUV, Van,
Wagon)
33 – UT Speeding Violation Study
Direct memos and reports to Commissioner, Bureau of Motor Vehicles, State of Utah
A random sample of 118 individuals given a speeding ticket in UT.
Numerical Variable of Interest:
Age at Incident = age (in years) of individual when given the speeding ticket
Numerical Predictor Variable:
Age at License = age (in years) of individual when license was obtained
Categorical Breakdown Variable:
Gender = gender of the individual given the speeding ticket
where “1” = Female, “0” = Male
Categorical Variable of Interest:
Road = type of road on which the speeding ticket was given (Backroad, City, Freeway)
34 – Wine Study
Direct memos and reports to the Editor, Food and Beverages, The New York Times.
A study of the characteristics of a random sample of 100 wines.
Numerical Variable of Interest:
Alcohol = alcoholic content (in %).
Numerical Predictor Variable:
Density = wine density measurement.
Categorical Breakdown Variable:
Type = type of wine: Red or White
Categorical Variable of Interest:
Quality Rating = 10-point scale quality rating:
where Low = 5 or Below, High = 6 or Above
35 – Zagat NYC Restaurant Study
Direct memos and reports to Editor, Food Section , The New York Times
A random sample of 66 NYC restaurants rated by Zagat with their characteristics.
Numerical Variable of Interest:
Cost$ = cost rating (in dollars)
Numerical Predictor Variable:
Décor&Service = combined décor and service rating (each on 1 to 30 scale)
Categorical Breakdown Variable:
Type Food = type of food
where “1” = Asian, “0” = Non-Asian
Categorical Variable of Interest:
HighPopIndx = whether the Zagat Popularity Index is 90 or higher (Yes, No)
