You can use the following basic syntax to calculate and plot a cumulative distribution function (CDF) in R:

#calculate empirical CDF of data p = ecdf(data) #plot CDF plot(p)

The following examples show how to use this syntax in practice.

**Example 1: Calculate & Plot CDF of Raw Data**

The following code shows how to calculate and plot a CDF of a random dataset in R:

#create some data data = rnorm(100) #calculate empirical CDF of data p = ecdf(data) #plot CDF plot(p, xlab='x', ylab='CDF', main='CDF of Data')

The x-axis shows the raw data values and the y-axis shows the corresponding CDF values.

**Example 2: Calculate & Plot CDF of Known Distribution**

The following code shows how to calculate and plot a CDF of the standard normal distribution:

curve(pnorm, from = -3, to = 3)

Alternatively, you can create the same plot using ggplot2:

library(ggplot2) ggplot(data.frame(x = c(-3, 3)), aes(x = x)) + stat_function(fun = pnorm)

**Additional Resources**

CDF vs. PDF: What’s the Difference?

How to Plot a CDF in Excel