clear

scalar p1 = normal(.4/sqrt(4/20))-normal(-.4/sqrt(4/20))
scalar p2 = normal(.4/sqrt(4/100))-normal(-.4/sqrt(4/100))
scalar p3 = normal(.4/sqrt(4/1000))-normal(-.4/sqrt(4/1000))
scalar list p1 p2 p3

drawnorm x, n(10000) means(5) sds(10)
gen p = x < 3.6
summarize x, detail
summarize p

scalar p = .4
scalar var = .4*(1- .4)

scalar p4 = 1 - normal((.43-.4)/sqrt(var/100))
scalar p5 = normal((.37-.4)/sqrt(var/400))
scalar list p var p4 p5 

scalar n = 24*(1.96/.01)^2
scalar p6 = normal((.41-.4)/sqrt(24/n)) -normal((.39-.4)/sqrt(24/n))
scalar list n p6

use http://www.learneconometrics.com/data/stata/Growth.dta, clear
scatter growth tradeshare

reg growth tradeshare
scalar pred1 = _b[_cons]+ _b[tradeshare]*.5
scalar pred2 = _b[_cons]+ _b[tradeshare]*1
scalar list pred1 pred2

reg growth tradeshare if country_name != "Malta"
scalar pred3 = _b[_cons]+ _b[tradeshare]*.5
scalar pred4 = _b[_cons]+ _b[tradeshare]*1
scalar list pred3 pred4