A brief Introduction to R

1. Download and install R and Rstudio

Visit http://cran.us.r-project.org

https://www.rstudio.com/products/rstudio/download/

2. play with R

• arithmetic operation

1+2

## [1] 3

3*4

## [1] 12

3/6

## [1] 0.5

3>5

## [1] FALSE

• use easy in-built functions

x <- c(12, 11, 16, 20)  # c standards for ?
?c
sum(x) 

## [1] 59

max(x)

## [1] 20

mean(x)

## [1] 14.75

median(x)

## [1] 14

sd(x)

## [1] 4.112988

var(x)

## [1] 16.91667

?mean

3. Get Data into R

• use import Dataset button in the top right cornor of Rstudio (discouraged) click the button, select the file you want to import.

• use read.table command

rm(list=ls())
mtcars <- read.table(file = "mtcars.csv", sep=",", header = T)  
# mtcars <- read.csv(file = "mtcars.csv")
?read.csv
?read.table
str(mtcars)

## 'data.frame':    32 obs. of  11 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : int  6 6 4 6 8 6 8 4 4 6 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : int  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : int  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : int  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: int  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: int  4 4 1 1 2 1 4 2 2 4 ...

?mtcars
mean(mtcars$mpg)

## [1] 20.09062

4. Visualize your data

# for numeric variable (1 or 2 variables)

hist(mtcars$mpg)

hist(mtcars$mpg, freq = FALSE) #density histogram

plot(density(mtcars$mpg))

plot(density(mtcars$disp))

boxplot(mtcars$mpg, horizontal = T)

stripchart(mtcars$mpg,method = 'jitter')

# two numerical variables
plot(mtcars$disp, mtcars$mpg, xlab ="displacement", ylab = "mile per gallon", main = "mpg vs. disp") # scatter plot

#abline(lm( mtcars$mpg ~ mtcars$disp ), col="red")

pairs(mtcars[,1:4]) # pairwise plot

# For categorial data 
counts = table(mtcars$cyl); barplot(counts)

boxplot(mtcars$mpg ~ mtcars$cyl)

boxplot(mtcars$hp ~ mtcars$cyl)

• Checking Normality

hist(mtcars$mpg)

qqnorm(mtcars$mpg)
qqline(mtcars$mpg)

set.seed(123)
x <- rnorm(100,1,2)
hist(x)

qqnorm(x)
qqline(x)

5. How to save the plot and use in the report later

• click on the plot (at bottom right corner usually)
• save the plot in .png or .pdf
• copy the plot into the report (in the future project)