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The ecdf() function in R is a useful tool for analyzing data by providing a graphical representation of the empirical cumulative distribution function (ECDF). This function plots the proportion of data points that are less than or equal to a given value, allowing for visual interpretation of the data’s distribution. This can be particularly helpful in identifying patterns, outliers, and the overall shape of the data. Furthermore, the ecdf() function allows for easy comparison of multiple datasets, making it a valuable tool for statistical analysis and decision making. Overall, the ecdf() function is a powerful tool for gaining insights into a dataset and understanding its underlying distribution.
Use ecdf() Function in R
You can use the ecdf function in R to calculate and plot an empirical cumulative distribution function.
Here is the most common way to use this function:
#calculate empirical cumulative distribution function of data p = ecdf(data) #plot empirical cumulative distribution function plot(p)
The following example shows how to use this function in practice.
Example: How to Use ecdf() Function in R
For this example, let’s create a vector of 1,000 random values that follow a :
#make this example reproducible set.seed(1)#create vector of 1,000 random values that follow standard normal distribution data = rnorm(1000) #view first six values in vector head(data) [1] -0.6264538 0.1836433 -0.8356286 1.5952808 0.3295078 -0.8204684
We can use the ecdf function to calculate the empirical cumulative distribution function of this dataset and then use the plot function to visualize it:
#calculate empirical cumulative distribution function of data p = ecdf(data) #plot empirical cumulative distribution function plot(p)
Note that you can also use the xlab, ylab and main arguments within the plot function to add an x-axis label, y-axis label and title to the plot, respectively:
#calculate empirical cumulative distribution function of data p = ecdf(data) #plot empirical cumulative distribution function with axis labels and title plot(p, xlab='x', ylab='CDF', main='CDF of Data')
The x-axis displays the values from the dataset.
The y-axis displays the cumulative distribution function.
Related:
Additional Resources
How to Plot a Normal Distribution in R
A Guide to dnorm, pnorm, qnorm, and rnorm in R
How to Perform a Shapiro-Wilk Test for Normality in R