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Table 9.1, page 302.
use http://www.ats.ucla.edu/stat/stata/examples/smss/crime, clear
list
sid state crime murder pctmetro pctwhite pcths poverty single
1. 1 ak 761 9 41.8 75.2 86.6 9.1 14.3
2. 2 al 780 11.6 67.4 73.5 66.9 17.4 11.5
3. 3 ar 593 10.2 44.7 82.9 66.3 20 10.7
4. 4 az 715 8.6 84.7 88.6 78.7 15.4 12.1
5. 5 ca 1078 13.1 96.7 79.3 76.2 18.2 12.5
6. 6 co 567 5.8 81.8 92.5 84.4 9.9 12.1
7. 7 ct 456 6.3 95.7 89 79.2 8.5 10.1
(data omitted)
48. 48 wi 264 4.4 68.1 92.1 78.6 12.6 10.4
49. 49 wv 208 6.9 41.8 96.3 66 22.2 9.4
50. 50 wy 286 3.4 29.7 95.9 83 13.3 10.8
51. 51 dc 2922 78.5 100 31.8 73.1 26.4 22.1
Figure 9.4, page 308.
graph twoway (scatter murder poverty if state ~= "md") /// (scatter murder poverty if state == "md", mlabel(state))
Table 9.2, page 310.
summarize murder poverty
Variable | Obs Mean Std. Dev. Min Max
-------------+-----------------------------------------------------
murder | 51 8.727451 10.71758 1.6 78.5
poverty | 51 14.25882 4.584242 8 26.4
regress murder poverty
Source | SS df MS Number of obs = 51
-------------+------------------------------ F( 1, 49) = 23.08
Model | 1839.06931 1 1839.06931 Prob > F = 0.0000
Residual | 3904.25223 49 79.6786169 R-squared = 0.3202
-------------+------------------------------ Adj R-squared = 0.3063
Total | 5743.32154 50 114.866431 Root MSE = 8.9263
------------------------------------------------------------------------------
murder | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
poverty | 1.32296 .2753711 4.80 0.000 .7695805 1.876338
_cons | -10.1364 4.120616 -2.46 0.017 -18.41708 -1.855707
------------------------------------------------------------------------------
Table 9.2, page 312.
regress murder poverty if state~="dc"
Source | SS df MS Number of obs = 50
-------------+------------------------------ F( 1, 48) = 31.36
Model | 307.342297 1 307.342297 Prob > F = 0.0000
Residual | 470.406476 48 9.80013492 R-squared = 0.3952
-------------+------------------------------ Adj R-squared = 0.3826
Total | 777.748773 49 15.8724239 Root MSE = 3.1305
------------------------------------------------------------------------------
murder | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
poverty | .5842405 .104327 5.60 0.000 .3744771 .7940039
_cons | -.8567153 1.527798 -0.56 0.578 -3.92856 2.215129
------------------------------------------------------------------------------
predict p2
predict resid, resid
sort sid
list murder p2 resid in 1/6
murder p2 resid
1. 9 4.459874 4.540126
2. 11.6 9.30907 2.290931
3. 10.2 10.8281 -.6280956
4. 8.6 8.140589 .4594117
5. 13.1 9.776463 3.323538
6. 5.8 4.927266 .8727344
Figure 9.6, page 311.
graph twoway (scatter murder poverty) (lfit murder poverty) (lfit murder poverty if state ~= "dc")
Figure 9.7, page 312.
graph twoway (scatter murder poverty if state ~= "dc") (lfit murder poverty if state ~= "dc") /// (scatter murder poverty if state == "la", mlabel(state))
Example 9.9, page 325.
regress murder poverty if state~="dc"
Source | SS df MS Number of obs = 50
-------------+------------------------------ F( 1, 48) = 31.36
Model | 307.342297 1 307.342297 Prob > F = 0.0000
Residual | 470.406476 48 9.80013492 R-squared = 0.3952
-------------+------------------------------ Adj R-squared = 0.3826
Total | 777.748773 49 15.8724239 Root MSE = 3.1305
------------------------------------------------------------------------------
murder | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
poverty | .5842405 .104327 5.60 0.000 .3744771 .7940039
_cons | -.8567153 1.527798 -0.56 0.578 -3.92856 2.215129
------------------------------------------------------------------------------
Table 9.4, page 329.
use http://www.ats.ucla.edu/stat/stata/examples/smss/hsales, clear
list
price size bdrms bathrms new
1. 48.5 1.1 3 1 no
2. 55 1.01 3 2 no
3. 68 1.45 3 2 no
(data omitted)
90. 150 2.04 3 3 no
91. 172.9 2.25 4 2 yes
92. 190 2.57 4 3 yes
93. 280 3.85 4 3 no
Tables 9.5 and 9.6, page 331; Example 9.11, page 332.
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
------------------------------------------------------------------------------
price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
size | 75.60684 3.865208 19.56 0.000 67.92908 83.2846
_cons | -25.19356 6.68845 -3.77 0.000 -38.47935 -11.90778
------------------------------------------------------------------------------
Figure 9.15, page 330.
graph twoway (scatter price size) (lfit price size), ylabel(0(50)300)
Table 9.7, page 335.
correlate crime murder poverty single if state~="dc"
(obs=50)
| crime murder poverty single
-------------+------------------------------------
crime | 1.0000
murder | 0.7815 1.0000
poverty | 0.3688 0.6286 1.0000
single | 0.6487 0.7281 0.4303 1.0000
pwcorr crime murder poverty single if state~="dc", sig
| crime murder poverty single
-------------+------------------------------------
crime | 1.0000
|
|
murder | 0.7815 1.0000
| 0.0000
|
poverty | 0.3688 0.6286 1.0000
| 0.0084 0.0000
|
single | 0.6487 0.7281 0.4303 1.0000
| 0.0000 0.0000 0.0018
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