Difference Between Probability Mass Function and Probability Density Function

Differences between the PMF and PDF is explained in the table below:

Characteristics	Probability Mass Function	Probability Density Function
Definition	The PMF is the probability that a discrete random variable takes at an exact value.	The PDF is the probability that a continuous random variable takes at a specified interval.
Type of Variable	The PMF deals with the discrete random variables.	The PDF deals with the continuous random variables.
Evaluation	PMF is evaluated at specific point.	PDF is evaluated at specified interval
Formula	f(x) = P (X = x)	P(x) = F'(x) where, F(x) is CDF

Probability Mass Function

Probability mass function i.e., PMF is the probability of discrete random variables with fixed values. In this article we will see the probability mass function along with the PMF definition, probability mass function examples, properties of probability mass function and probability mass function formulas.

We will also discuss the probability mass function table and graph, the difference between the probability mass function and probability density function and solve some examples related to the probability mass function. Let’s start our learning on the topic “Probability Mass Function”.

Table of Content

What is Probability Mass Function?

Probability Mass Function Definition
Probability Mass Function Example

Probability Mass Function Formulas

Probability Mass Function Formula in Binomial Distribution
Probability Mass Function Formula in Poisson Distribution