4  Console

4.1 R interface

In contrast to many other statistical software packages that use a point-and-click interface, e.g. SPSS, JMP, Stata, etc, R has a command-line interface. The command line has a command prompt, e.g. >, see below.

>

This means, that you will be entering commands on this command line and hitting enter to execute them, e.g. 

help()

Use the up arrow to recover past commands.

hepl()
help() # Use up arrow and fix

4.2 R GUI (or RStudio)

Most likely, you are using a graphical user interface (GUI) and therefore, in addition, to the command line, you also have a windowed version of R with some point-and-click options, e.g. File, Edit, and Help.

In particular, there is an editor to create a new R script. So rather than entering commands on the command line, you will write commands in a script and then send those commands to the command line using Ctrl-R (PC) or Command-Enter (Mac).

a = 1 
b = 2
a + b

[1] 3

Multiple lines can be run in sequence by selecting them and then using Ctrl-R (PC) or Command-Enter (Mac).

4.3 Intro Activity

One of the most effective ways to use this documentation is to cut-and-paste the commands into a script and then execute them.

Cut-and-paste the following commands into a new script and then run those commands directly from the script using Ctrl-R (PC) or Command-Enter (Mac).

x <- 1:10
y <- rep(c(1,2), each=5)
m <- lm(y~x)
s <- summary(m)

Now, look at the result of each line

x
y
m
s
s$r.squared

Click for solution

x

 [1]  1  2  3  4  5  6  7  8  9 10

y

 [1] 1 1 1 1 1 2 2 2 2 2

m

Call:
lm(formula = y ~ x)

Coefficients:
(Intercept)            x  
     0.6667       0.1515  

s

Call:
lm(formula = y ~ x)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.4242 -0.1667  0.0000  0.1667  0.4242 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)   
(Intercept)   0.6667     0.1880   3.546  0.00756 **
x             0.1515     0.0303   5.000  0.00105 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.2752 on 8 degrees of freedom
Multiple R-squared:  0.7576,    Adjusted R-squared:  0.7273 
F-statistic:    25 on 1 and 8 DF,  p-value: 0.001053

s$r.squared

[1] 0.7575758