q-q plot

A q-q plot is a plot of the quantiles of one dataset against the quantiles of a second dataset. This is often used to understand if the data matches the standard statistical framework, or a normal distribution.

If the data is normally distributed, the points in the q-q plot follow a straight diagonal line. This is useful to check for normality at a glance but note that it is not an accurate statistical test. In the video, you saw how to create a q-q plot using the qqnorm() function, and how to create a reference line for if the data were perfectly normally distributed with qqline():

> qqnorm(amazon_stocks,
         main = "AMAZON return QQ-plot")

> qqline(amazon_stocks,
         col = "red")

In the context of this course, the first dataset is Apple stock return and the second dataset is a standard normal distribution. In this exercise, you will check how Apple stock returns in rtn deviate from a normal distribution.

This exercise is part of the course

Visualizing Time Series Data in R

View Course

Exercise instructions

Draw a q-q plot for rtn titled "Apple return QQ-plot"
Add a reference line in red for the normal distribution using qqline()

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Create q-q plot


# Add a red line showing normality

Edit and Run Code