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Just to confirm we it would be $18 and you would submit to me
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Then I would pay you.
Here is the HW:
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 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:
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
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.
Price
Sq. Feet
Age
Bedrooms
Bathrooms
Garage _
110000
1000
28
3
1
1
133500
1400
23
3
1
1
Price = Last selling price
112500
1248
58
3
4
1
Sq. Feet = square footage of the house
141750
1106
12
2
1
1
Age = Age of the house as of now
195250
2112
78
2
6
2
Bedrooms = number of bedrooms in the house
132250
1078
33
2
1
1
Bathrooms = number of bathrooms in the house
136000
952
13
2
3
2
Garage = number of cars that can be garaged
162750
1100
1
2
1
2
148500
1040
17
3
1
2
123500
1416
27
4
2
1
142250
1150
25
3
2
2
145500
1220
17
3
2
2
155250
1464
28
3
2
2
150750
1228
15
3
2
2
150900
1132
1
3
4
2
144000
1132
1
3
4
2
151900
1132
1
3
4
2
161500
1464
29
3
3
2
155750
1270
1
4
3
2
157250
1362
23
3
4
2
152900
1120
1
3
3
2
145250
1025
1
3
5
2
164750
1290
19
3
3
2
152500
1260
22
3
4
2
150750
1085
1
3
4
2
144750
1312
41
3
4
2
148250
1489
34
3
4
1
174500
1540
24
3
4
2
215500
2112
12
4
4
2
155750
1351
1
4
5
2
167900
1351
1
4
4
2
148500
1193
5
3
4
2
152500
1200
1
4
4
2
167200
1256
1
3
4
2
159500
1058
1
3
4
2
153600
1210
13
3
4
2
168000
1380
1
3
4
2
166100
1301
7
3
4
2
165200
1375
8
3
4
2
174900
1437
8
3
4
2
160250
1330
1
3
4
2
165100
1361
1
3
4
2
170500
1594
16
3
3
2
155900
1186
2
3
4
2
167700
1336
1
3
4
2
165400
1325
5
3
4
2
163500
1352
9
3
4
2
178500
1354
7
3
2
2
164000
1318
1
3
4
2
172750
1415
9
3
4
2
149000
1337
2
3
4
2
176000
2028
25
4
4
2
205500
1820
21
3
4
2
181100
1330
2
3
4
2
166600
1356
1
3
4
2
168750
1350
2
3
3
2
188700
1523
1
4
4
2
190600
1477
1
3
5
2
160900
1185
4
3
4
2
164900
1430
22
3
4
3
154700
1311
1
3
4
2
184750
1411
4
3
4
2
174000
1412
1
3
4
2
136250
1300
6
3
4
2
169000
1334
4
3
4
2
151900
1360
19
3
4
2
180350
1900
43
3
2
2
171300
1328
1
3
4
2
172650
1350
1
3
4
2
174750
1601
1
3
5
2
166900
1405
1
3
4
2
171750
1619
9
3
4
2
170900
1450
2
3
4
2
168400
1818
1
4
4
2
193100
1424
1
3
4
3
206900
2240
16
4
6
2
193000
1872
2
4
4
2
188500
1550
1
4
4
3
168300
1342
1
3
4
2
157100
1318
1
3
4
2
177650
1843
1
3
4
2
207100
1526
1
3
4
3
191900
1526
1
3
4
3
164250
1407
1
3
4
2
146100
1515
1
3
4
2
136750
1425
1
3
4
2
226600
2150
20
4
4
2
182250
1430
2
3
4
2
158900
1975
19
4
6
2
173000
1433
8
3
4
2
217600
2400
34
5
4
3
201000
2160
32
4
4
2
149650
1600
10
3
5
2
206150
1526
1
3
4
3
162500
1480
20
3
4
2
138250
129
1
4
5
3
172900
1493
1
3
4
3
188400
1728
4
3
5
2
182750
1828
1
3
4
2
175500
1689
1
4
4
2
157500
1572
1
4
4
2
211900
1534
1
3
4
3
207300
1775
10
4
6
2
126750
608
4
3
5
2
181200
1938
22
4
5
2
181500
1564
5
4
4
2
152750
1700
22
3
4
2
183200
1393
2
3
4
2
161400
1500
9
3
3
2
160300
1510
5
3
3
2
163900
1689
1
4
4
2
179900
1407
1
3
4
2
188900
1938
25
4
4
2
201750
1337
1
3
4
3
200500
1590
8
3
4
3
176300
1488
1
3
4
2
195300
1526
1
3
4
3
194350
1594
1
3
4
3
199100
1609
1
4
4
3
207400
1212
1
3
4
3
185300
1812
1
4
6
3
157500
1773
9
4
6
3
214300
1838
20
4
4
3
233900
2672
20
3
5
2
145100
1008
2
4
4
2
181750
1700
5
4
5
2
196900
2080
22
5
4
2
125800
1235
3
4
6
2
197900
1800
22
4
6
2
200400
1661
1
3
4
3
173300
1680
9
3
5
2
193100
1700
1
3
4
2
166100
1707
3
4
4
2
182750
1595
1
4
6
3
164500
1420
1
4
5
3
196500
1618
5
3
5
2
227200
1632
5
3
4
3
191200
1558
1
3
4
3
219400
1770
7
3
3
2
199750
2072
29
4
5
2
203900
2012
24
4
4
2
199500
1899
1
4
4
3
168100
1572
1
3
4
2
190500
1672
6
3
4
3
208800
1611
1
3
4
3
228700
1920
3
4
6
3
228900
2367
22
4
6
2
194200
1934
13
3
4
2
250100
2712
22
4
4
2
224600
2144
23
4
5
2
211250
2040
23
3
6
2
161500
1622
1
4
4
3
159800
1665
1
3
4
3
132400
2192
26
4
5
2
229250
2358
21
4
6
2
159700
1738
4
4
4
2
211700
1933
7
4
4
3
199250
2194
12
3
6
2
194750
2050
3
4
6
3
147750
2256
25
4
4
2
208900
2600
30
5
4
2
246600
1687
1
3
4
3
186600
1968
21
4
6
2
194200
1650
5
4
4
2
126500
1646
1
4
4
3
178000
1860
2
4
5
2
240800
2536
21
4
6
2
225750
1866
1
4
5
3
166500
2020
14
4
6
2
207900
1875
6
4
5
2
260650
1910
9
4
4
3
245750
2546
25
4
6
2
112600
1400
36
3
5
2
185100
2878
29
6
6
2
235500
3000
11
5
6
2
179900
1776
8
4
5
3
265750
3024
18
5
6
2
222600
2682
20
5
6
2
242500
2037
6
4
6
3
156500
1836
8
4
4
2
253850
1733
3
3
5
3
209500
2700
19
4
7
2
224500
1651
2
3
4
4
204250
2700
22
4
6
2
237800
2051
12
3
3
2
226500
2090
3
4
6
3
199500
2700
42
5
3
2
216750
2182
1
4
4
3
181250
2600
37
5
3
1
229500
1930
1
3
4
3
207500
1834
2
3
4
3
206250
1933
1
3
4
3
265400
2172
1
3
4
3
219250
2193
4
3
4
2
272100
2018
1
4
5
4
229600
2310
1
4
5
3
261000
2256
1
4
4
3
274600
2710
20
4
4
3
192400
1984
1
3
4
3
217200
2443
1
4
5
3
201700
2650
2
4
7
2
243350
2560
1
5
6
3
287700
2341
1
4
6
4
240750
2259
1
4
6
3
217500
2167
1
4
4
3
288900
2383
1
4
7
3
265500
2544
1
3
5
3
253750
2518
1
4
5
3
208150
1991
1
4
4
3
229700
2400
15
4
5
3
282300
2939
1
5
5
3
234750
2500
3
4
5
3
170200
2854
1
5
5
3
301200
3080
12
4
6
3
305900
3659
1
4
6
3
225400
2542
6
4
6
3
251900
2208
2
5
5
3
291300
2939
1
5
5
3
301700
2460
1
4
5
3
262750
2619
1
4
5
3
273900
2718
10
4
5
3
317800
3403
1
6
6
3
242000
2619
1
4
5
3
298500
3550
13
4
6
3
229500
2644
5
4
5
3
302100
2867
1
4
5
3
310500
2938
1
4
5
4
273100
3321
12
5
7
2
305700
2975
1
5
8
3
289900
3063
1
4
6
3
257500
2754
1
4
6
3
311000
3285
8
5
7
3
280300
3300
12
5
6
3
328150
2893
1
4
5
4
337300
3277
1
5
6
3
265500
3160
27
5
7
2
231000
2750
4
4
5
3
274800
2727
4
4
5
3
262500
2733
1
5
5
3
361100
4080
14
6
7
3
322900
2900
2
5
6
3
310500
3469
1
5
8
3
226000
3000
3
4
6
2
309300
2950
1
4
5
3
298600
3217
3
4
6
4
278000
2300
43
3
4
3
331000
2418
5
3
4
4
317000
3255
3
4
6
3
302900
3114
10
3
5
4
58700
1098
30
3
1
1
71100
948
28
2
1
1
59800
1159
50
2
1
1
78500
1200
23
3
2
1
64200
1430
54
3
1
1
57600
1217
23
3
1
1
54100
911
49
2
1
2
72000
954
53
2
1
2
90100
950
48
2
1
2
75200
1086
41
3
5
2
58500
1180
7
3
1
1
64700
1004
52
2
1
2
88900
988
28
3
1
2
76550
1661
45
4
3
1
82250
1008
47
2
1
2
68600
1400
31
3
1
1
75900
1340
34
2
4
1
79600
1563
44
3
4
1
88600
1072
49
2
1
2
92700
1534
19
4
4
1
80350
1016
21
3
1
2
83400
1040
16
3
3
2
97200
1136
29
3
2
2
96300
1282
42
3
4
2
78100
1670
47
3
1
1
94000
1530
54
4
4
2
79300
1789
53
3
4
1
88150
1339
65
2
1
2
88200
1160
21
3
1
2
91600
1910
47
4
4
1
82700
1100
6
3
4
2
91100
1379
40
3
4
2
91800
1032
15
2
1
2
96450
1672
29
3
1
1
72950
1407
37
3
2
2
82200
1450
40
3
3
2
93300
1728
61
4
1
2
111400
1976
37
4
4
1
90250
1608
7
3
1
1
72500
1532
41
3
2
2
70600
1288
5
3
4
2
65950
1320
9
3
4
2
90100
1416
41
2
4
2
110200
2022
36
4
3
1
122500
1550
42
3
2
2
93900
1568
40
3
3
2
84800
1968
40
3
3
1
103600
1536
22
3
4
2
121000
1872
39
4
4
2
102150
2200
31
4
4
1
129600
1763
29
3
4
2
82950
2073
71
3
3
2
111700
1563
52
3
1
3
127150
2080
28
5
4
2
139300
1968
47
3
3
2
111900
1340
9
3
4
3
96400
1730
12
3
4
2
106250
2168
2
4
4
1
126100
2320
22
4
4
1
121950
1750
8
3
4
2
150950
2000
39
3
4
2
142100
2073
44
3
2
2
173200
2000
20
3
3
2
157850
1900
45
3
6
3
164700
2400
38
4
4
2
130100
3000
43
4
5
1
123900
2172
1
5
6
3
180500
2515
51
2
4
2
169900
2500
49
4
6
3
213000
2345
44
5
4

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