Using the data in SLEEP$75.$RAW, we obtain the estimated equation:maleageageedutotwrksleep $75\mathrm{.}87128\mathrm{.}70\mathrm{.}2871\mathrm{.}11163\mathrm{.}83\mathrm{.}840,32+++=$

$(235\mathrm{.}11)(\mathrm{.}018)(5\mathrm{.}86)(11\mathrm{.}2)(\mathrm{.}134)(34\mathrm{.}33)$

n $=706,$ R$2=0\mathrm{.}123,117\mathrm{.}2=$R

The variable sleep is total minutes per week spent sleeping at night, totwrk is total weekly

minutes spent working, edu and age are measured in years, and male is a gender dummy.

a$.$ All other factors being equal, is there evidence that men sleep more than women? How

strong is the evidence?

b$.$ Is there a statistically significant tradeoff between working and sleeping? What is the

estimated tradeoff?

c$.$ What other regressions do you need to run to test the null hypothesis that, holding other

factors fixed, age has no effect on sleeping?

$2.$ The following equations were estimated using the data in BWGHT$.$RAW:whitemaleparitycfacigsbwght $045\mathrm{.}034\mathrm{.}017.)$minlog$(00110\mathrm{.}0052\mathrm{.}65\mathrm{.}4)$log$(++++=$

$(\mathrm{.}38)(\mathrm{.}0010)(\mathrm{.}0085)(\mathrm{.}006)(\mathrm{.}011)(\mathrm{.}015)$

n $=1,388,$ R$2=0\mathrm{.}0472$whitemaleparitycfacigsbwght $055\mathrm{.}027\mathrm{.}016.)$minlog$(0093\mathrm{.}0044\mathrm{.}66\mathrm{.}4)$log$(++++=$

$(\mathrm{.}22)(\mathrm{.}0009)(\mathrm{.}0059)(\mathrm{.}006)(\mathrm{.}010)(\mathrm{.}013)$fatheducmotheduc $0032\mathrm{.}0030.+$

$(\mathrm{.}0030)(\mathrm{.}0026)$

n $=1,191$ R$2=0\mathrm{.}0493$

where bwght is the birth weight in pounds, cigs denote average number of cigarettes the

mother smoked per day during pregnancy, parity is the birth order of this child, faminc

denotes annual family income, motheduc denotes years of schooling for the mother, and

fatheduc is the number of years of schooling for the father. We have added a dummy

variable for whether the child is male and a dummy variable indicating whethe the child

is classified as white.