QQ-plots: Quantile-Quantile plots - R Base Graphs

Previously, we described the essentials of R programming and provided quick start guides for importing data into R.

Here, we’ll describe how to create quantile-quantile plots in R. QQ plot (or quantile-quantile plot) draws the correlation between a given sample and the normal distribution. A 45-degree reference line is also plotted. QQ plots are used to visually check the normality of the data.

Pleleminary tasks

  1. Launch RStudio as described here: Running RStudio and setting up your working directory

  2. Prepare your data as described here: Best practices for preparing your data and save it in an external .txt tab or .csv files

  3. Import your data into R as described here: Fast reading of data from txt|csv files into R: readr package.

Example data

Here, we’ll use the built-in R data set named ToothGrowth.

# Store the data in the variable my_data
my_data <- ToothGrowth

Create QQ plots

The R base functions qqnorm() and qqplot() can be used to produce quantile-quantile plots:

  • qqnorm(): produces a normal QQ plot of the variable
  • qqline(): adds a reference line
qqnorm(my_data$len, pch = 1, frame = FALSE)
qqline(my_data$len, col = "steelblue", lwd = 2)

It’s also possible to use the function qqPlot() [in car package]:


As all the points fall approximately along this reference line, we can assume normality.


This analysis has been performed using R statistical software (ver. 3.2.4).

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