Model A Model c . regress SBP i.village Source MS MS 381 0.6577 .0133 Adj R-squa

Question

Model A Model c . regress SBP i.village Source MS MS 381 0.6577 .0133 Adj R-squared-0.0052 25.783 3336.32719 7 476.618171 Prob > F Mode22980.3184 Residual 228313.671 373 664.765851 R-squared 379 602.18742 R-squared 251293.99 380 661.299972 Root MSE 0.0891 251293.99 380 661.299972 Root MSE 195% conf. Interval] t P>It] [95% Conf. Interval 94358 14.35152 14.30208 17.08335 14.02417 10.03007 4893 e.326 5.984756 6.081754 3.375 5.582195 5.66849 5.733491 5.772061 2 6.114988 -1.16886 5.695304 9.089286 6.306127 5.974867 -7.601517 7.958863 -5.616368 -10.02417 -12.36779 -3.310732 6784493 cons 133.0096 1.257432 105.78 0.0 130.5372 135.482 5146198 .0833211 6.18 0.000 3507904 Juan Sanchez Altagrac Los Gueneos San Antonio 838 129.625 4.557843 0e0 120 138.5873 cons . regress SBP age i.sex df regress sB age 1.sex 1.vittage 6948 Residua 225795.895 2 12749.0474 Prob F 378 597.343637 R-sqared . 1025 0.0967 MS Adj R-squared = 27598.1374 223695.852 9 3066.45971 Prob >F 371 602.953779 R-squared 380 661.299972 Root MSE 0.1098 51293.99 38 661.299972 Root MSE 24.555 SBP t P> | t I 195% Conf. Interval] 195% conf. Interval 5642883 0864251 3943542 7342224 5S2506 0871658 3811049 723907 sex -5.727008 2.789532 .05 0.041 -11.21195 242064 99.55401 115.9942 -5.585589 2.846715 -11.18331 0121314 107.7741 4.180562 25.78 0.000 4.94172 5.806355 2.476232 5.318357 2.247755 5.420892 4.877723 5.516077 1.873748 5.826942 .5588276 5.436059 6.91397 0.85 .395 -6.475774 16.35921 Carmona -8.411772 -5.968975 12.90728 15.72442 Juan Sanchez La Altagracia Los Gueneos San Antonio -11.24818 -4.670358 10.13052 18.98113 7.155386 105.6328 5.893864 94.04328 2224 . regress SBP age i.sex agesex Model 26243.5819 Residual 225050.408 3 8747.86064 ProbF 377 596.950683 R-squared Adj R-squared 0.0973 251293.99 380 661.299972 Root MSE SBP Std [95% Conf. Interval] 6298259 .1 1044211 4245053 8351466 4.919118 9.926412 -.207772 104.8213 4.944407 21.20 0.000 24.43719 1578066 0.50 0.620 -14.59895 1859243 1.12 0.264 -.5733506 95 , 09926 agesex cons

Explanation / Answer

1) From MODEL A SBP Agec:

Intercept= 133.0096

2) From Model B: Women aged 48

Y'= 107.7741 + 0.5642883*Age - 5.727008*Male

Y'= 10.7741 + 0.5642883*48 - 5.727008*0

Y'= 134.8599

3) Answer B: Village is not good predictor of mean SBP

All explanatory variables are not significant to an output variables. If variable is significant, then it is good for prediciton.

Multicollinearity issue occurs when explonatory variables are highely significant to an output variable.

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