Answer Happy

Based on the linear probability model of working from Question 5, test the following hypothesis at a=5%: H_O: B_smoking>=0 and H_a: B_smoking< 0. Use p-values.
Based on the linear probability model of working from Question 5, test the following hypothesis at a=5%: H_O: B_smoking>=0 and H_a: B_
smoking< 0. Use p-values.
You are modeling linear probability model of developing cancer as a function of demographic characteristics and life-style choices for a sample of Baby Boomers, where Cancer a dummy that takes value 1 if a person was ever diagnosed with cancer and zero otherwise female a dummy that takes value 1 for a female and 0 for a male age age of a respondent measured in years inc10k household's income measured in $10,000 married a dummy variable that takes value 1 if a person is married and 0 otherwise smoking a dummy variable that takes value 1 if a person ever smoked and 0 otherwise phys_active= a dummy variable that takes value 1 if a person is physically active and 0 otherwise 30 af 49.57743372 19,944 -110946714 19,972 513790834 Prob>F Ad) R-spared Boot H 19,973 84.32 0.0000 0.0253 0.0250

age female 1 married i smoking phys_active | -.0138593 incl0k | 0002592 0044793 0004443 0073392 0281039 cons I -.1845142 married f smoking I phys active | inc10k 1 Obs 19,973 19,973 19,973 19,973 19,973 AM. KEE. 19,973 19,973 0002104 0050875 20.51 0.000 0.09 0.930 1.40 0.162 5.74 0.000 -2.73 0.006 0002363 1.10 0.273 0175361 -10.52 0.000 sum cancer age female married smoking phys active inclők if e (sample)-1 Variable | Std. Dev. cancer | age | female 1 0052529 0048997 .0050809 Mean 1309268 66.55004 .5857408 .6309017 .5739248 .378511 6.062572 .3373287 11.49664 .492606 .4825727 .4945173 195% cont. Intervall 0049073 0104161 0176352 .0377077 -.0039003 0007224 -.1501419 .485028 10.38617 0040512 -.0095276 -.0029568 0185001 -20238183 -.0002041 --2188864 Min 0 1000 24 Max 107 1 1 1 0 0 353.6642 1