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log: C:\AAA Miker Files\newer web pages\soc_meth_proj3\section5_2009.log
log type: text
opened on: 24 Feb 2009, 15:27:26
. edit
(8 vars, 11 obs pasted into editor)
- preserve
*Here above I copied the Anscombe data from Excel to the Stata data editor, then preserved, then closed the data editor window.
. graph matrix x1 x2 x3 x4 y1 y2 y3 y4
. twoway (scatter y1 x1)
. twoway (scatter y1 x1) (lfit y1 x1)
. twoway (scatter y4 x4) (lfit y4 x4)
. regress y4 x4
Source | SS df MS Number of obs = 11
-------------+------------------------------ F( 1, 9) = 18.00
Model | 27.4900007 1 27.4900007 Prob > F = 0.0022
Residual | 13.7424908 9 1.52694342 R-squared = 0.6667
-------------+------------------------------ Adj R-squared = 0.6297
Total | 41.2324915 10 4.12324915 Root MSE = 1.2357
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y4 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x4 | .4999091 .1178189 4.24 0.002 .2333841 .7664341
_cons | 3.001727 1.123921 2.67 0.026 .4592411 5.544213
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. rvfplot
. rvfplot, yline(0)
. twoway (scatter y2 x2) (lfit y2 x2)
. rvfplot, yline(0)
. regress y2 x2
Source | SS df MS Number of obs = 11
-------------+------------------------------ F( 1, 9) = 17.97
Model | 27.5000024 1 27.5000024 Prob > F = 0.0022
Residual | 13.776294 9 1.53069933 R-squared = 0.6662
-------------+------------------------------ Adj R-squared = 0.6292
Total | 41.2762964 10 4.12762964 Root MSE = 1.2372
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y2 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x2 | .5 .1179638 4.24 0.002 .2331475 .7668526
_cons | 3.000909 1.125303 2.67 0.026 .4552978 5.54652
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. rvfplot, yline(0)
. *the rvfplot, residual versus fit plot, is a post-estimation command that you can use after regression.
. exit, clear