econ 140b

econ 140b -...

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. 3. regress price sqrft bdrms, robust Linear regression Number of obs = 88 F( 2, 85) = 27.25 Prob > F = 0.0000 R-squared = 0.6319 Root MSE = 63.045 ------------------------------------------------------------------------------ | Robust price | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- sqrft | .1284362 .0195909 6.56 0.000 .0894843 .1673882 bdrms | 15.19819 8.943735 1.70 0.093 -2.58435 32.98073 _cons | -19.315 41.5205 -0.47 0.643 -101.8689 63.2388 . 3. E) test sqrft=bdrms=0 ( 1) sqrft - bdrms = 0 ( 2) sqrft = 0 F( 2, 85) = 27.25 Prob > F = 0.0000
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. 3. F) test sqrft=bdrms ( 1) sqrft - bdrms = 0 F( 1, 85) = 2.84 Prob > F = 0.0958 .
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4. A) regress lprice lsqrft bdrms llotsize, robust Linear regression Number of obs = 88 F( 3, 84) = 49.32 Prob > F = 0.0000 R-squared = 0.6430 Root MSE = .1846 ------------------------------------------------------------------------------ | Robust lprice | Coef. Std. Err. t P>|t| [95% Conf. Interval]
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Unformatted text preview: -------------+----------------------------------------------------------------lsqrft | .7002324 .1038288 6.74 0.000 .4937574 .9067074 bdrms | .0369584 .0306011 1.21 0.231 -.0238953 .0978121 llotsize | .1679667 .0414734 4.05 0.000 .0854922 .2504412 _cons | -1.297042 .7813145 -1.66 0.101 -2.850771 .2566876------------------------------------------------------------------------------. 4. B) regress lprice bdrms, robust level(90) Linear regression Number of obs = 88 F( 1, 86) = 21.06 Prob > F = 0.0000 R-squared = 0.2148 Root MSE = .27056------------------------------------------------------------------------------| Robust lprice | Coef. Std. Err. t P>|t| [90% Conf. Interval]-------------+----------------------------------------------------------------bdrms | .1672261 .0364391 4.59 0.000 .1066364 .2278158 _cons | 5.036487 .1203273 41.86 0.000 4.836411 5.236563------------------------------------------------------------------------------....
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econ 140b -...

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