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Lecture 10

MGCR 271 Lecture Notes - Watt, Simple Linear Regression, Confidence Interval
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5 Pages
73 Views
Fall 2017

Department
Management Core
Course Code
MGCR 271
Professor
Glenn Zabowski
Lecture
10

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1
Inference for Simple Regression
Condo Sales Data Set:
The following are characteristics of a sample of sales of units in a condominium:
CONDOMINIUM SALES
UNIT
DATE
PRICE ($)
FLOOR #
AREA (m)
PARKING
SPACES
BATH-
ROOMS
1
01-09-01
188,000
7
117
0
1
2
02-10-16
226,000
7
117
1
2
3
02-04-07
203,700
4
117
2
2
4
02-08-28
245,100
10
117
2
2
5
02-02-01
229,000
10
117
2
2
6
02-10-25
244,000
11
117
1
1
7
02-02-01
204,000
5
117
2
2
8
02-10-15
242,500
10
117
2
1
9
02-10-19
235,800
7
117
2
2
10
02-07-01
229,600
12
117
1
1
11
01-11-01
212,600
12
117
1
1
12
02-10-06
200,000
3
117
0
2
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2
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.6261771
R Square
0.392097761
Adjusted R Square
0.331307537
Standard Error
15858.73387
Observations
12
ANOVA
df
SS
MS
F
P-Value
Regression
1
1622174766
1622174766
6.45001343
0.029378882
Residual
10
2514994401
251499440.1
Total
11
4137169167
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
189693.5331
13405.19029
14.15075273
6.11328E-08
159824.9079
219562.1583
Floor
3918.138801
1542.76404
2.539687664
0.029378882
480.6463185
7355.631284
RESIDUAL OUTPUT
Observation
Predicted Y
Residuals
1
217120.5047
-29120.50473
2
217120.5047
8879.495268
3
205366.0883
-1666.088328
4
228874.9211
16225.07886
5
228874.9211
125.0788644
6
232793.0599
11206.94006
7
209284.2271
-5284.227129
8
228874.9211
13625.07886
9
217120.5047
18679.49527
10
236711.1987
-7111.198738
11
236711.1987
-24111.19874
12
201447.9495
-1447.949527
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Description
Inference for Simple Regression Condo Sales Data Set: The following are characteristics of a sample of sales of units in a condominium: CONDOMINIUM SALES UNIT DATE PRICE ($) FLOOR # AREA (m) VIEW PARKING BATH- SPACES ROOMS 1 01-09-01 188,000 7 117 lake 0 1 2 02-10-16 226,000 7 117 lake 1 2 3 02-04-07 203,700 4 117 street 2 2 4 02-08-28 245,100 10 117 lake 2 2 5 02-02-01 229,000 10 117 lake 2 2 6 02-10-25 244,000 11 117 street 1 1 7 02-02-01 204,000 5 117 street 2 2 8 02-10-15 242,500 10 117 lake 2 1 9 02-10-19 235,800 7 117 lake 2 2 10 02-07-01 229,600 12 117 street 1 1 11 01-11-01 212,600 12 117 street 1 1 12 02-10-06 200,000 3 117 street 0 2 1SUMMARY OUTPUT Regression Statistics Multiple R 0.6261771 R Square 0.392097761 Adjusted R Square 0.331307537 Standard Error 15858.73387 Observations 12 ANOVA df SS MS F P-Value Regression 1 1622174766 1622174766 6.45001343 0.029378882 Residual 10 2514994401 251499440.1 Total 11 4137169167 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 189693.5331 13405.19029 14.15075273 6.11328E-08 159824.9079 219562.1583 Floor 3918.138801 1542.76404 2.539687664 0.029378882 480.6463185 7355.631284 RESIDUAL OUTPUT Observation Predicted Y Resi
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