Today let’s re-create two variables and see how to plot them and include a regression line. 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(176, 154, 138, 196, 132, 176, 181, 169, 150, 175)`

Now let’s take bodymass to be a variable that describes the masses (in kg) of the same ten people. Copy and paste the following code to the R command line to create the weight variable.

`bodymass <- c(82, 49, 53, 112, 47, 69, 77, 71, 62, 78)`

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

`height`

bodymass

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

`plot(bodymass, height)`

We can enhance this plot using various arguments within the `plot()`

command. Copy and paste the following code into the R workspace:

`plot(bodymass, height, pch = 16, cex = 1.3, col = "blue", main = "HEIGHT PLOTTED AGAINST BODY MASS", xlab = "BODY MASS (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 using `lm()`

on the two variables by adding the following text at the command line:

`lm(height ~ bodymass)`

We see that the intercept is 98.0054 and the slope is 0.9528. By the way – `lm`

stands for “linear model”.

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

`abline(98.0054, 0.9528)`

Another line of syntax that will plot the regression line is:

`abline(lm(height ~ bodymass))`

None of this was so difficult! In our next blog we will look again at regression.

David

#### Annex: R codes used

[code lang="r"]<br />

# Create the height variable.<br />

height <- c(176, 154, 138, 196, 132, 176, 181, 169, 150, 175)</p>

<p># Create the weight variable.<br />

bodymass <- c(82, 49, 53, 112, 47, 69, 77, 71, 62, 78)</p>

<p># View both variables.<br />

height<br />

bodymass </p>

<p># Create a scatterplot of height against bodymass variable.<br />

plot(bodymass, height)</p>

<p># Create more complete scatterplot of height against bodymass variable.<br />

plot(bodymass, height, pch = 16, cex = 1.3, col = "blue", main = "HEIGHT PLOTTED AGAINST BODY MASS", xlab = "BODY MASS (kg)", ylab = "HEIGHT (cm)")</p>

<p># Perform a linear regression on the two variables.<br />

lm(height ~ bodymass)</p>

<p># Add a best fit line (regression line) to the plot.<br />

abline(98.0054, 0.9528)</p>

<p># Alternatively we can plot the regression line using the following syntax:<br />

abline(lm(height ~ bodymass))<br />

[/code]