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Normal Probability Plot in R using ggplot2

  • Last Updated : 24 Feb, 2021

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)
  
# ploting 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)
  
# ploting 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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