Cumulative Distribution Function

Cumulative Distribution Function
Description	The Cumulative Distribution Function (CDF) helps to learn about the distribution of data by calculating the cumulative probability of a given variable value in a dataset.
Why to use	To calculate the probability of a given variable value by trying to fit it with different distribution functions.
When to use	For numerical variables having positive or negative values.	When not to use	—
Prerequisites	The data should not contain any missing values.
Input	Numerical variable having any positive or negative value.	Output	CDF curve Cumulative Probability Function predicted by CDF
Statistical Methods used	Cumulative Probability	Limitations	It can be used only on numerical data.

CDF takes input as a random variable value (either discrete or continuous) and then determines the cumulative probability of that variable. By default, the data is sorted and then sent to the algorithm. Also, in the output Data tab, the resultant data appears in a sorted manner.