Visualizing bivariate relationships
If you want to go even further than simply plotting variables and instead investigate whether any relationship exists between 2 variables, you can draw a scatterplot. This is a graph where the values of two variables are plotted along two axes.
The pattern of the resulting points is used to reveal the presence of any correlation; usually, a regression line is added to identify the tendency, if there is any:
- An upward sloping regression line indicates a positive linear relationship between A and B (when A goes up B tends to goes up as well)
- A downward sloping regression line indicates a negative linear relationship between A and B
You can draw a scatterplot and then create a regression model with the following functions:
plot(x = A, y = B)
lm(B ~ A)
In this exercise, you will draw a scatterplot and regression line for the return series for the SP500 (sp500
) and Citigroup (citi
) from January 2015 to January 2017, both of which are provided in your workspace
This exercise is part of the course
Visualizing Time Series Data in R
Exercise instructions
- Draw a scatterplot with
sp500
on the x-axis andciti
on the y-axis. - Add a regression line of
citi
againstsp500
usinglm()
andabline()
.- Specify the regression as the
reg
argument toabline()
. - Make this line red and twice as thick as the default.
- Specify the regression as the
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Draw the scatterplot
# Draw a regression line