Exercise

# 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

Instructions

**100 XP**

- Draw a scatterplot with
`sp500`

on the x-axis and`citi`

on the y-axis. - Add a regression line of
`citi`

against`sp500`

using`lm()`

and`abline()`

.- Specify the regression as the
`reg`

argument to`abline()`

. - Make this line red and twice as thick as the default.

- Specify the regression as the