Normal Probability Plot in R using ggplot2
A normal probability plot is a graphical representation of the data. A normal probability plot is used to check if the given data set is normally distributed or not. It is used to compare a data set with the normal distribution. If a given data set is normally distributed then it will reside in a shape like a straight line.
In this article, we are going to use ggplot2 with qqplotr to plot and check if the dataset is normally distributed using qqplot only.
Approach
- Install the following necessary libraries by pasting them in r console
install.packages(“ggplot2”)
install.packages(“qqplotr”)
- Create a random data set with a different mean and standard deviation that you want to plot.
- Plotting data using stat_qq_point() method.
- Plotting data points with line using stat_qq_line() function.
Given below is a proper implementation using the above approach
Example 1: Plotting data using stat_qq_point() method.
R
# importing libraries library (ggplot2) library (qqplotr) # creating random data random_values = rnorm (500, mean = 90, sd = 50) # plotting data without line and labels ggplot (mapping = aes (sample = random_values)) + stat_qq_point (size = 2) |
Output:

Fig. 1 Plotting Data points.
Example 2: Plotting data points with line using stat_qq_line() function.
R
# importing libraries library (ggplot2) library (qqplotr) # creating random data random_values = rnorm (500, mean = 90, sd = 50) # plotting data with proper labels # And adding line with proper properties ggplot (mapping = aes (sample = random_values)) + stat_qq_point (size = 2,color = "red" ) + stat_qq_line (color= "green" ) + xlab ( "x-axis" ) + ylab ( "y-axis" ) |
Output:

Fig. 2 Adding normal line
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