I wanted to avoid advanced topics in this post and focus on
some “blocking and tackling” with R in an effort to get novices started. This is some of the basic code I found useful
when I began using R just over 6 weeks ago.

Reading in data from a .csv file is a breeze with this
command.

> data = read.csv(file.choose())

No need to have your own data set as R comes with data
packages already.

> data() #list the
datasets available in R

> # load the dataset 'cars' and display the variables

> data(cars)

> head(cars)

speed dist

1 4 2

2 4 10

3 7 4

4 7 22

5 8 16

6 9 10

#the command head() gives shows we have two variables, car
speed and stopping distance along with the first 6 rows of data

#using attach() splits the data into separate columns and
avoids having to use what I feel is the pesky $

> attach(cars)

# descriptive statistics of our two variables

> summary(cars)

speed dist

Min. : 4.0 Min.
: 2.00

1st Qu.:12.0 1st Qu.: 26.00

Median :15.0 Median : 36.00

Mean :15.4
Mean : 42.98

3rd Qu.:19.0 3rd Qu.: 56.00

Max. :25.0
Max. :120.00

> # univariate plots for speed