4a

library(dplyr)
library(magrittr)
library(ggplot2)

 c(3, 5) %>% mean()

## [1] 4

  liida <- function(arv1, arv2){
    arv1+arv2
  }

  3 %>% liida(4)

## [1] 7

mtcars %>% group_by(am) %>% summarise(keskmine=mean(mpg)) %>%  ggplot(aes(x=am, y=keskmine)) + geom_point()

 select(mtcars, mpg)$mpg %>% mean()

## [1] 20.09062

(mpg~hp) %>% plot(mtcars)
plot(mpg~hp, mtcars)

mtcars[mtcars$am == 1,] %$% mean(mpg)

## [1] 24.39231