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  3. Visualizing Time Series Data in R

Exercise

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.

Instructions

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