A discrete distribution describes the probability of outcomes of a discrete random variable, which can take on a finite or countably infinite number of values. It is characterized by a probability mass function that assigns probabilities to each possible outcome, ensuring that the sum of all probabilities equals one.

Discrete Distribution

discrete distribution

probability of outcomes

A discrete random variable is like a magical number box that only holds certain numbers, like 1, 2, or 3, and each number has its own special chance of being picked. It's like rolling a dice where you know exactly what numbers can come up, and each number has a chance of happening.

discrete random variable

Finite number of values

countably infinite number of values

A Probability Mass Function (PMF) provides the probability that a discrete random variable is exactly equal to a specific value, serving as a fundamental tool for understanding discrete probability distributions. It is essential for calculating probabilities, expected values, and variances, and forms the basis for more complex statistical analyses involving discrete data.

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