object.size(mtcars)
dim(mtcars)
sapply(mtcars, class)
head(mtcars)
summary(mtcars)
boxplot(mpg~am, data=mtcars, xlab="Transmission", ylab="mpg")
title(main= ("manual=1 & autom=0"))

fit1 <- lm(mpg~ am, data = mtcars)
summary(fit1)$coefficients

##              Estimate Std. Error   t value     Pr(>|t|)
## (Intercept) 17.147368   1.124603 15.247492 1.133983e-15
## am           7.244939   1.764422  4.106127 2.850207e-04

fit2 <- lm(mpg~ ., data = mtcars)
fit2 <- step(fit2, direction = "both")

summary(fit2)$coefficients

##              Estimate Std. Error   t value     Pr(>|t|)
## (Intercept)  9.617781  6.9595930  1.381946 1.779152e-01
## wt          -3.916504  0.7112016 -5.506882 6.952711e-06
## qsec         1.225886  0.2886696  4.246676 2.161737e-04
## am           2.935837  1.4109045  2.080819 4.671551e-02

anova(fit1, fit3)

## Analysis of Variance Table
## 
## Model 1: mpg ~ am
## Model 2: mpg ~ wt + qsec + am
##   Res.Df    RSS Df Sum of Sq      F   Pr(>F)    
## 1     30 720.90                                 
## 2     28 169.29  2    551.61 45.618 1.55e-09 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1