Probability Distribution describes how the possible values of a random variable are distributed along with their chances of occurring. It helps us understand the likelihood of different outcomes and forms the foundation of statistics, data analysis, and many real-life applications.
Foundations
Start here to understand the basics of probability distributions, random variables, probability functions, expected value, and variance.
- Introduction to Probability Distribution
- Random Variable
- Discrete Random Variable
- Probability Distribution Function
- Probability Mass Function (PMF)
- Probability Density Function (PDF)
- Expected Value and Variance
Discrete Distributions
Learn about probability distributions with countable outcomes using PMF, including Bernoulli, Binomial, Geometric, Poisson, and Uniform distributions.
- Discrete Probability Distribution
- Bernoulli Trials and Binomial Distribution
- Binomial Distribution
- Binomial Mean and Standard Deviation
- Variance of Binomial Distribution
- Geometric Distribution
- Geometric Distribution Formula
- Poisson Distribution
- Uniform Distribution
- Binomial vs Poisson Distribution
Continuous Distributions
Understand probability distributions with continuous outcomes using PDF, including Normal, Uniform, and other important continuous distributions.
- Continuous Probability Distributions
- Normal Distribution
- Standard Normal Distribution
- Z-Score Table
- How to Find Probability Using Mean and Variance
- How to Find Probability Between Two Z-Scores
- Normal vs Non-Normal Distribution
- Continuous vs Discrete Uniform Distribution
- Continuous Probability Distributions
- Coefficient of Skewness
- Positively Skewed Distribution
- Negatively Skewed Distribution
Quick Revision and Practice
Strengthen your understanding with revision notes, solved examples, and practice problems on random variables and probability distributions.