Qnt. 5040 – Mini Report #1
Regressions
Dr. Phillip S. Rokicki
Maximum Points: 5
Excel File Needed: The Prescott Housing Study
The Prescott County Housing Problem
Introduction:
The Prescott county mayor, Robert (Pete) Smith has been worried for some time that housing values in the county have been declining. Pete said to the county commission recently,
“Our housing stock is getting so old and tired, and I’m afraid that if we don’t start building new homes that our children will just move away to Orlando or even to, heaven forbid, to South Florida. I think that we need to study this situation, and do something about it right now!”
What Pete did not say, but each of the commissioners knew, was that his brother-in-law, Bo Bradley is a developer who wants the commission to rezone 350 acres in the north county for a new development. This land is currently envisioned to be a county park, but old Bo want to develop it. Bo said recently, “What this county needs is my development, not some old park for the deer.” Bo it seems is interested in making money more than he is in protecting undeveloped land.
In order to get this study going Pete has asked you to look at some recent sales of homes in the county to understand what is going on with the housing stock, and then to project out what kind of values that five typical housing could bring. What he is hoping is that the values will be so low that the commission will want to rezone those 350 acres for Bo’s development.
Using the Excel data file that has been provided you are to completely answer the following questions:
1. What is the current status of the housing stock in the county?
a. To do this you will create a one-variable summary using StatTools and analyze the age of the recently sold homes, their average price sold, the number of bedrooms, bathrooms and number of cars that can be garaged.
b. What does the skewness and kurtosis tell you about these data?
c. Would it be better to use the Interquartile range to analyze this data (not a yes or no answer) and if so why, or why not?
2. Doing two Q-Q plots, do you consider the data for price and square footage to be normal or not, and why?
3. Doing a correlation in StatTools and using all six of the variables, how are each of these variables correlated to each other. Again be specific.
4. Doing a scatterplot of price versus square footage and adding a trend line to the plot, what does this tell you about the data?
a. Now do a scatterplot of price versus age and adding a trend line, what does this tell you about the question of new homes versus price?
5. Next do a multiple regression using price as the dependent variable, and all other variables as independent variables:
a. Do any of the variables have a t-value that is greater than the alpha (.05) for this assignment? If so, delete them and rerun the regression and compare and contrast the old regression versus the new regression without one or more of the variables.
b. Is the F-ratio ...
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Qnt. 5040 – Mini Report #1RegressionsDr. Phillip S. RokickiM.docx
1. Qnt. 5040 – Mini Report #1
Regressions
Dr. Phillip S. Rokicki
Maximum Points: 5
Excel File Needed: The Prescott Housing Study
The Prescott County Housing Problem
Introduction:
The Prescott county mayor, Robert (Pete) Smith has been
worried for some time that housing values in the county have
been declining. Pete said to the county commission recently,
“Our housing stock is getting so old and tired, and I’m afraid
that if we don’t start building new homes that our children will
just move away to Orlando or even to, heaven forbid, to South
Florida. I think that we need to study this situation, and do
something about it right now!”
What Pete did not say, but each of the commissioners knew, was
that his brother-in-law, Bo Bradley is a developer who wants
the commission to rezone 350 acres in the north county for a
new development. This land is currently envisioned to be a
county park, but old Bo want to develop it. Bo said recently,
“What this county needs is my development, not some old park
for the deer.” Bo it seems is interested in making money more
than he is in protecting undeveloped land.
In order to get this study going Pete has asked you to look at
some recent sales of homes in the county to understand what is
going on with the housing stock, and then to project out what
kind of values that five typical housing could bring. What he is
hoping is that the values will be so low that the commission will
2. want to rezone those 350 acres for Bo’s development.
Using the Excel data file that has been provided you are to
completely answer the following questions:
1. What is the current status of the housing stock in the county?
a. To do this you will create a one-variable summary using
StatTools and analyze the age of the recently sold homes, their
average price sold, the number of bedrooms, bathrooms and
number of cars that can be garaged.
b. What does the skewness and kurtosis tell you about these
data?
c. Would it be better to use the Interquartile range to analyze
this data (not a yes or no answer) and if so why, or why not?
2. Doing two Q-Q plots, do you consider the data for price and
square footage to be normal or not, and why?
3. Doing a correlation in StatTools and using all six of the
variables, how are each of these variables correlated to each
other. Again be specific.
4. Doing a scatterplot of price versus square footage and adding
a trend line to the plot, what does this tell you about the data?
a. Now do a scatterplot of price versus age and adding a trend
line, what does this tell you about the question of new homes
versus price?
5. Next do a multiple regression using price as the dependent
variable, and all other variables as independent variables:
a. Do any of the variables have a t-value that is greater than the
alpha (.05) for this assignment? If so, delete them and rerun the
regression and compare and contrast the old regression versus
the new regression without one or more of the variables.
b. Is the F-ratio for this/these regressions significant? Why?
c. Is the r-squared values for this/these regressions appear to be
valid? Does it show that it explained a sufficient amount of the
total variation?
6. Using the coefficients from this regression estimate the
selling prices for the following typical Prescott county homes:
3. Home
number
Square footage
Age of the home
Number of bedrooms
Number of bathrooms
Size of the garage (cars)
Projected Selling Price (determined by you)
1
1,850
25
3
2
1
2
2,200
14
4
3
2
3
3,000
5
5
4
3
4
3,400
5
5
5
3
4. 5
2,200
40
3
2
1
7. Based on the projected selling price of these homes, will
Mayor Pete convince the county commission to rezone the land
for his brother-in-law, or does the county get a new park?
Defend your answer based on the statistics that you have
calculated in this case study. Your argument should be no more
than 300 words.
Submit your mini report by the date indicated in the
weekly/monthly calendar for your section.
# # #
Copyright R&A 2014 Page 2
C
opyright R&A 2014
Page
1
Qnt. 5040
–
Mini
Report #1
5. Regressions
Dr.
Phillip S. Rokicki
Maximum Points:
5
Excel File Needed:
The Prescott Housing Study
The Prescott County Housing Problem
Introduction:
The
Prescott
county mayor
, Robert (Pete) Smith has been worried for some time that
housing
values in the county have been declining. Pete said to the
county commission recently,
“
Our housing stock is getting
so
old and tired, and I
’
m afraid that if we don
’
t start
6. building new homes that our children will just move away to
Orlando or even to,
heaven forbid, to South Florida. I think that we need to study
this situation, and do
so
mething about it
right now!
”
What Pete did not say, but each of the commissioners knew, was
that his brother
-
in
-
law, Bo
Bradley is a developer who wants the commission to rezone 350
acres
in the
north
county for a
new development. This land is currently envisioned to be a
county par
k
, but old Bo want to
develop it.
Bo said recently,
“
What this county needs is my development,
not some old park
for
the deer
.
”
7. Bo it seems is interested in making money more than he is in
protecting undeveloped
land.
In order to get this study going
Pete
has
asked you to look at some recent sales of homes in the
county to understand what is going on with the hous
ing stock, and then to project out what kind
of values that
f
ive typical
housing c
ould bring. What he is h
oping is that the values will be so
low that the commission will want to rezone those 350 acres for
Bo
’
s development.
Using the Excel data file that has been provided you are to
completely answer the foll
owing
questions:
1.
What is the current status of the housing stock in the county?
8. a.
To do this you will create a
one
-
variable summary
using StatTools and analyze
the age of the recently sold homes, their average price sold, the
number of
bedrooms, bathrooms a
nd number of cars that can be garaged.
b.
What does the skewness and kurtosis tell you about th
e
se
data?
c.
Would it be better to use the Interquartile range to analyze this
data (not a yes or
no answer) and if so why, or why not?
2.
Doing
t
wo
Q
-
Q plot
9. s
, do you conside
r the data for price and square footage to be normal
or not, and why?
3.
Doing a
correlation
in StatTools and using all six of the variables, how are each of
these
variables correlated to each other. Again be specific.
4.
Doing a
scatterplot
of price versus squ
are footage and adding a trend line to the plot,
what does this tell you about the data?
Copyright R&A 2014 Page 1
Qnt. 5040 – Mini Report #1
Regressions
Dr. Phillip S. Rokicki
Maximum Points: 5
Excel File Needed: The Prescott Housing Study
The Prescott County Housing Problem
Introduction:
The Prescott county mayor, Robert (Pete) Smith has been
10. worried for some time that housing
values in the county have been declining. Pete said to the
county commission recently,
“Our housing stock is getting so old and tired, and I’m afraid
that if we don’t start
building new homes that our children will just move away to
Orlando or even to,
heaven forbid, to South Florida. I think that we need to study
this situation, and do
something about it right now!”
What Pete did not say, but each of the commissioners knew, was
that his brother-in-law, Bo
Bradley is a developer who wants the commission to rezone 350
acres in the north county for a
new development. This land is currently envisioned to be a
county park, but old Bo want to
develop it. Bo said recently, “What this county needs is my
development, not some old park for
the deer.” Bo it seems is interested in making money more than
he is in protecting undeveloped
land.
In order to get this study going Pete has asked you to look at
some recent sales of homes in the
county to understand what is going on with the housing stock,
and then to project out what kind
of values that five typical housing could bring. What he is
hoping is that the values will be so
low that the commission will want to rezone those 350 acres for
Bo’s development.
Using the Excel data file that has been provided you are to
completely answer the following
questions:
11. 1. What is the current status of the housing stock in the county?
a. To do this you will create a one-variable summary using
StatTools and analyze
the age of the recently sold homes, their average price sold, the
number of
bedrooms, bathrooms and number of cars that can be garaged.
b. What does the skewness and kurtosis tell you about these
data?
c. Would it be better to use the Interquartile range to analyze
this data (not a yes or
no answer) and if so why, or why not?
2. Doing two Q-Q plots, do you consider the data for price and
square footage to be normal
or not, and why?
3. Doing a correlation in StatTools and using all six of the
variables, how are each of these
variables correlated to each other. Again be specific.
4. Doing a scatterplot of price versus square footage and adding
a trend line to the plot,
what does this tell you about the data?
Sheet1PriceSq. FeetAgeBedroomsBathroomsGarage
_110000100028311133500140023311Price = Last selling
price112500124858341Sq. Feet = square footage of the
house141750110612211Age = Age of the house as of
now195250211278262Bedrooms = number of bedrooms in the
house132250107833211Bathrooms = number of bathrooms in
the house13600095213232Garage = number of cars that can be
garaged1627501100121214850010401731212350014162742114
22501150253221455001220173221552501464283221507501228
15322150900113213421440001132134215190011321342161500
14642933215575012701432157250136223342152900112013321
45250102513521647501290193321525001260223421507501085
13421447501312413421482501489343411745001540243422155
00211212442155750135114521679001351144214850011935342
