In Part 1 we installed R and used it to create a variable and summarise it using a few simple commands. Today let’s re-create that variable and also create a second variable, and see what we can do with them.

As before, we take `height`

to be a variable that describes the heights (in cm) of ten people. Copy and paste the following code to the R command line to create this variable.

`height = c(186, 165, 149, 206, 143, 187, 191, 179, 162, 185)`

Now let’s take `weight`

to be a variable that describes the weights (in kg) of the same ten people. Copy and paste the following code to the R command line to create the `weight`

variable.

`weight = c(89, 56, 60, 116, 51, 75, 84, 78, 67, 85)`

Both variables are now stored in the R workspace. To view them, enter:

`height`

weight

We can now create a simple plot of the two variables as follows:

`plot(weight, height)`

However, this is a rather simple plot and we can embellish it a little. Copy and paste the following code into the R workspace:

`plot(weight, height, pch = 16, cex = 1.3, col = "red", main = "My first plot using R", xlab = "Weight (kg)", ylab = "Height (cm)")`

In the above code, the syntax `pch = 16`

creates solid dots, while `cex = 1.3`

creates dots that are 1.3 times bigger than the default (where `cex = 1`

). More about these commands later.

Now let’s perform a linear regression on the two variables by adding the following text at the command line:

`lm(height ~ weight)`

We see that the intercept is 102.7071 and the slope is 0.9539.

Finally, we can add a best fit line to our plot by adding the following text at the command line:

`abline(102.7071, 0.9539)`

None of this was so difficult! 🙂

In Part 3 we will look again at regression and create more sophisticated plots.

David

#### Annex: R codes used

# Creating the height variable height = c(186, 165, 149, 206, 143, 187, 191, 179, 162, 185) # Creating the weight variable weight = c(89, 56, 60, 116, 51, 75, 84, 78, 67, 85) # Show content of both variables height weight # Create a graph (scatterplot) for two variables plot(weight, height) # Improved scatterplot for two variables plot(weight, height, pch = 16, cex = 1.3, col = "red", main = "My first plot using R", xlab = "Weight (kg)", ylab = "Height (cm)") # Estimating the simple linear regression lm(height ~ weight) # Adding regression line on the existing graph abline(102.7071, 0.9539)

Screenshots of the R console with all results:

Senior Academic Manager in *New Zealand Institute of Sport* and Director of *Sigma Statistics and Research Ltd*. Author of the book: *R Graph Essentials*.