A Cumulative Distribution Function (CDF) is a statistical function that shows the probability of a random variable being less than or equal to a given value. It is commonly used to describe the probability distribution of a continuous random variable.
A Probability Density Function (PDF) describes the probability of a random variable taking on a specific value. In contrast, a CDF shows the probability of a random variable being less than or equal to a given value. Essentially, the CDF is the integral of the PDF.
The range of values for a CDF is between 0 and 1. This represents the probability of a random variable being less than or equal to a given value. The CDF starts at 0 for the lowest possible value and ends at 1 for the highest possible value.
A CDF is commonly used in statistical analysis to calculate the probability of a random variable falling within a certain range of values. It is also used to compare different probability distributions and to determine the likelihood of a certain outcome.
A CDF can be graphed by plotting the cumulative probabilities on the y-axis and the corresponding values of the random variable on the x-axis. The resulting curve is called a CDF curve and can be used to visualize the distribution of the random variable.