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day8prs

# day8prs - PADP 8120 Data Analysis and Sta5s5cal Modeling...

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3/8/11 1 PADP 8120: Data Analysis and Sta5s5cal Modeling Ordinary Least Squares PRACTICE Spring 2011 Angela Fer5g, Ph.D. Graphing a fiCed line (setup) . use "/Users/afertig/Documents/Teaching/PADP8120/day7-associations/day7f.dta” . set seed 50234 . drop if hstat==. (27 observations deleted) . drop if faminc>200000 (306 observations deleted) . drop if faminc==0 (41 observations deleted) . bsample 10 . scatter hstat faminc || lfit hstat faminc . list hstat faminc | hstat faminc | |----------------------| 1. | Very Good 2 18642 | 2. | Good 3 48600 | 3. | Very Good 2 161900 | 4. | Good 3 22000 | 5. | Good 3 26000 | |----------------------| 6. | Excellent 1 104000 | 7. | Very Good 2 22002 | 8. | Fair 4 60500 | 9. | Very Good 2 152790 | 10. | Excellent 1 75200 |

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3/8/11 2 Y-­૒intercept looks like about 2.8 and the slope is about .3/50000=0.000006 OLS in Stata . reg hstat faminc Source | SS df MS Number of obs = 10 -------------+------------------------------ F( 1, 8) = 1.25 Model | 1.09104954 1 1.09104954 Prob > F = 0.2968 Residual | 7.00895046 8 .876118808 R-squared = 0.1347 -------------+------------------------------ Adj R-squared = 0.0265 Total | 8.1 9 .9 Root MSE = .93601 ------------------------------------------------------------------------------ hstat | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- faminc | 0.297 _cons | .4975333 5.52 0.001 1.598961 3.893589 ------------------------------------------------------------------------------ Let’s calculate by hand (using excel) all of the numbers in red.
3/8/11 3 Make this table for the coeﬃcients

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day8prs - PADP 8120 Data Analysis and Sta5s5cal Modeling...

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