#Since we are only using the lung data we will use the attach function for lung.

attach(lung)

#regression equation on p. 125.
#first generating ffev1a = ffev1/100.
ffev1a <- ffev1/100

lm1 <- lm(ffev1a ~ fheight, lung)
summary(lm1)

#summary stats, middle p. 127.
subset.male <- data.frame(fage, fheight, ffev1a)

apply(subset.male, 2, mean)
apply(subset.male, 2, stdev)
apply(subset.male, 2, range) 

#regression equation, p. 127.
lm2 <- lm(ffev1a ~ fage+fheight, lung)
summary(lm2)

#covariance matrix, p. 133.
subset2 <- data.frame(fage, fheight, fweight, ffev1a)
var(subset2, na.method="omit")
cor(subset2, na.method="omit")

#table 7.2, p. 138.
aov2 <- aov(ffev1a ~ fage+fheight, lung)
summary(aov2)
 
#table 7.5, males only.
apply(subset.male, 2, mean)
apply(subset.male, 2, stdev)

male.lm <- lm(ffev1a ~ fage+fheight, lung)
summary(male.lm)

mfev1a <- mfev1/100
subset.female <- data.frame(mage, mheight, mfev1a)

apply(subset.female, 2, mean)
apply(subset.female, 2, stdev)

female.lm <- lm(mfev1a ~ mage+mheight, lung)
summary(female.lm)

detach(lung)

#using the lung.long data set for the regression model including 
#males and females

apply(lung.long, 2, mean)
apply(lung.long, 2, stdev)

lm.all <- lm(fev1a ~ age+height, lung.long)
summary(lm.all)