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(Solved) PEOPLE BOXES, INC. - APARTMENT COMPLEX CONSORTIUM PLANNING EXPANSION BASED ON DEMOGRAPHIC CHANGES - BRIEF People Boxes, Inc. is a consortium of real...


I need help in a Business Stats project. I am ok with understanding the data, however, I am having a lot of trouble with F-tests for joint significance, proportions, and residual plots. I am doing part 5, Attachment #1 is the instructions and attachment #2 is the data. Please follow the steps and refer to the data. If anyone could help me with this project I'd greatly appreciate it! Our professor didn't tell us anything else besides post these instructions online and we're all having a really hard time. This project is due soon, so help would be most appreciated as soon as possible!! :) thanks!!!

PEOPLE BOXES, INC.
- APARTMENT COMPLEX CONSORTIUM PLANNING
EXPANSION BASED ON DEMOGRAPHIC CHANGES
- BRIEF
People Boxes, Inc. is a consortium of real estate owners who seek out
growing real estate demand among young, affluent, highly-educated
workers entering the workforce or relocating to new cities. They
specialize in condominium-style new construction, saving on costs by
reusing blueprints in different cities and working with national
contracting firms. Their revenue growth depends on identifying new
markets to expand into, filling a niche in high-demand, high-income
cities.
They have collected data on demographics and income in a number of
metropolitan statistical areas (MSAs) in the United States and would like
assistance in analyzing the data to provide some background
information and some conclusions on the underlying relationships of
income and age, education levels, and rental prevalence, as well as the
determinants and effects of the supply of housing stock. 1. Youth
- Are America’s “young” cities poorer than the median US
income? For this, define “young” as “between 14 and 24”, and
find the proportion of each MSA that is young. Then split the
data into 2 groups. Test to see if the average median
household income in the youngest MSAs is lower than the
median of median household incomes.
- What is the mean of median HH incomes for the older half of
cities? Come up with a confidence interval estimate of the
population mean.
- Do America’s “young” cities have more rental properties than
the average US city? Find the average number of rental units - for all US MSAs and then test to see if the average number of
rental units of the “young” cities is lower than the overall US
city average.
Will our tenants need dedicated high-speed internet access?
How many people work from home in “young” cities? Find an
interval estimate for the average number of people who
work from home.
Does the number of people who work from home in “young”
cities differ from the national average? Test to find out.
Draw any conclusions and make any recommendations you’d
like to offer your client. 2. Retirement
- Does income vary with retirement? For this, define “retirees”
as “people age 65 and up”, and find the proportion of each
city that is retirees. Then split the data into 2 groups. Test to
see if there’s a difference in household income between the
MSAs with the most and least retirees per capita.
- Is a “work-from-home” attitude less common in retirement
age cities? Do the proportions of citizens that work from
home vary between “old cities” and other cities. Use the two
groups to test if this proportion is lower in “old” cities than in
other cities.
- Is there more of a vested interest at stake in the real estate
market in “old” cities? Is the proportion of properties that are
owner-occupied greater in “old” cities? Use these two groups
to test for a difference between these proportions.
- Do retirees prefer smaller cities? Test to see if the total
population is lower in “old” cities than in other cities.
- Is household size different in “old” cities? For each city, find
the average household size and then test to see if this differs
across the two groups.
- Draw any conclusions and make any recommendations you’d
like to offer your client. 3. Education
- Are cities with college and graduate school enrollment more
income-diverse or less so? For this, find the proportion of
each city that is currently enrolled in college, graduate, or
professional school. Then split the data into 2 groups
a. Test to see if there’s a difference in average
household incomes between the MSAs with the most
and least proportions of the population in
postsecondary education.
b. Test to see if there’s a difference in the variance in
household incomes between the MSAs with the most
and least proportions of the population in
postsecondary education.
- Do cities with college and graduate school enrollment have
more rental property?
a. Test to see if there’s a difference in the number of
renter-occupied housing units between the MSAs
with the most and least proportions of the population
in postsecondary education.
b. Test to see if there’s a difference in the variance in
the number of renter-occupied housing units across
cities between the two groups.
- Do cities with college and graduate school enrollment have
more high-earning households? For this, find the proportion
of households in each city that earns $100,000 or more.
a. Test to see if there is a difference in the average
representation of high-earning households between
the MSAs with the most and least proportions of the
population in postsecondary education.
b. Test to see if there’s a difference in the variance in
high-earning households between the two groups of
cities.
- Draw any conclusions and make any recommendations you’d
like to offer your client.
- 4. Rental Property
- For this, find the proportion of each city’s housing stock that
is currently renter-occupied.
- Use regression methods to address each of the following
models:
- The percentage of the housing stock that is renter-occupied
depends on
a. the percentage of the population that is young.
b. the percentage of the population that is retirement
age.
c. the percentage of the population that is enrolled in
college or graduate school.
- Which model is better between a, b, and c? What variables
are significant? What is your interpretation?
- Household income depends on
a. the percentage of the housing stock that is renteroccupied.
b. the percentage of the housing stock that is renteroccupied and the housing stock per capita.
c. the percentage of the housing stock that is renteroccupied, the percentage of the population that is
retirement age, and the housing stock per capita.
- Draw any conclusions and make any recommendations you’d
like to offer your client. 5. Some full models
- What are the determinants of household income? To examine
this we will need to create some new variables: Youth: define “young” as “between 14 and 24”, and find
the proportion of each MSA that is young Retirement: For this, define “retirees” as “people age 65
and up”, and find the proportion of each city that is
retirees. Education: find the proportion of each city that is
currently enrolled in college, graduate, or professional
school Rental intensity: find the proportion of each city’s
housing stock that is currently renter-occupied Housing stock per capita: the number of housing units
per person in a city.
Consider two models:
a. a model that posits that income depends on the
retirement age (the best predictor of the above variables)
b. a model that includes youth, retirement, education, rental
intensity, and the per-capita housing stock as
independent variables. Does model a or b perform better? Use an F test
for joint significance of a subset of variables to
see which model should be preferred. Consider the residual plots. Are there any
problems with these regressions? What are your interpretations of the preferred
model?
What are the determinants of the available housing stock per
capita? Consider two models:
a. A model that posits that housing stock per capita
depends on retirement
b. A model that includes youth, retirement, education, and
rental intensity as independent variables. Does model a or b perform better? Use an F test
for joint significance of a subset of variables to
see which model should be preferred. Consider the residual plots. Are there any
problems with these regressions? What are your interpretations of the preferred
model? Draw any conclusions and make any
recommendations you’d like to offer your client. - -

 


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