Simple Regression Analysis of Agresti & Finlay data from Table 9.4
[Stata Program]
use http://www.gseis.ucla.edu/courses/data/hsales
describe
summarize price size
plot price size
correlate price size
regress price size
predict yhat
predict resid, residual
predict zresid, rstandard
graph price yhat size, connect(.s)
more
stem zresid
graph zresid, histogram normal bin(15)
qnorm zresid
sort zresid
list size price zresid in 1/5
list size price zresid in -5/l
rvpplot size, yline(0)
rvfplot, yline(0)
drop if price >=250
regress price sizeÊ
plot price sizeÊ
predict zresid2, rstandard
graph zresid2,histogram normal bin(15)
[Stata Output]
. describe
Contains data from http://www.gseis.ucla.edu/courses/data/hsales.dta
obs: 93
vars: 5 7 Dec 1999 15:53
size: 2,232 (98.1% of memory free)
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1. price float %9.0g sell price in 1,000's
2. size float %9.0g sq feet in 1,000's
3. bdrms float %9.0g number bedrooms
4. bathrms float %9.0g number bathrooms
5. new float %9.0g nl new house?
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Sorted by:
. summarize price size
Variable | Obs Mean Std. Dev. Min Max
---------+-----------------------------------------------------
price | 93 99.53333 44.18413 17.5 309.4
size | 93 1.649677 .5252607 .4 3.85
. plot price size
309.4 +
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+----------------------------------------------------------------+
.4 sq feet in 1,000's 3.85
. correlate price size
(obs=93)
| price size
---------+------------------
price | 1.0000
size | 0.8988 1.0000
. regress price size
Source | SS df MS Number of obs = 93
---------+------------------------------ F( 1, 91) = 382.63
Model | 145097.459 1 145097.459 Prob > F = 0.0000
Residual | 34508.4029 91 379.213218 R-squared = 0.8079
---------+------------------------------ Adj R-squared = 0.8058
Total | 179605.862 92 1952.23763 Root MSE = 19.473
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price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
size | 75.60684 3.865208 19.561 0.000 67.92908 83.2846
_cons | -25.19356 6.68845 -3.767 0.000 -38.47935 -11.90778
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. predict yhat
. predict resid, residual
. predict zresid, rstandard
. graph price yhat size, connect(.s)
. stem zresid
Stem-and-leaf plot for zresid (Standardized residuals)
zresid rounded to nearest multiple of .01
plot in units of .01
-3** | 03
-2** | 69
-2** | 36
-1** | 93,68
-1** | 46,32,26,13,07,03,02,01
-0** | 93,85,85,84,84,83,75,72,72,57,55,54
-0** | 49,47,43,38,38,38,38,37,34,33,29,21,19,18,11,10,06
0** | 05,05,06,07,11,13,15,20,21,22,28,31,33,33,33,36,36,37,43,48,49,49
0** | 53,54,56,57,58,59,66,69,69,72,74,78,81,93,93,94,95
1** | 02,04,09,10,10,10,13,14,17,26,46
1** |
2** |
2** |
3** |
3** |
4** |
4** | 65
. graph zresid, histogram normal bin(15)
. qnorm zresid
. sort zresid
. list size price zresid in 1/5
size price zresid
1. 3.05 149 -3.033176
2. 1.28 19.6 -2.691249
3. 2.1 88.1 -2.357733
4. 1.74 69 -1.929348
5. 2.4 124 -1.684739
. list size price zresid in -5/l
size price zresid
89. 1.43 105 1.140879
90. 1.62 120 1.172573
91. 1.15 86 1.258087
92. 2.25 172.9 1.455004
93. 3.3 309.4 4.652866
. rvpplot size, yline(0)
. rvfplot, yline(0)
drop if price>=250
. regress price size
Source | SS df MS Number of obs = 91
-------------+------------------------------ F( 1, 89) = 268.65
Model | 76106.4446 1 76106.4446 Prob > F = 0.0000
Residual | 25212.8979 89 283.290988 R-squared = 0.7512
-------------+------------------------------ Adj R-squared = 0.7484
Total | 101319.342 90 1125.77047 Root MSE = 16.831
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price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
size | 65.6568 4.005764 16.39 0.000 57.69743 73.61617
_cons | -10.29033 6.676088 -1.54 0.127 -23.55558 2.974911
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. plot price size
190 +
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+----------------------------------------------------------------+
.4 sq feet in 1,000's 3.05
. predict zresid2, rstandard
. graph zresid2,histogram normal bin(15)
