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This video introduces the notion of a random variable "X". Random variables are similar to standard variables in calculus, except ...

In this video, learn the concepts of Cumulative Distribution Function (CDF) and Probability Density Function (PDF) for a Random ...

One of the most important concepts in probability is that of a function of a random variable. For example, the mean and variance ...

The expected value (aka the mean) of a probability distribution is one of the most important functions of a random variable.

In this video, we explain the concept of a Uniform Random Variable — one of the simplest and most important probability ...

This video computes probability from the probability density function of a Continuous Random Variable using the Integral button in ...

The joint probability distribution quantifies the joint dependence between two random variables, X and Y. If these random ...

The moment generating function is an important advanced concept in probability. Much like functions can be expanded in a Taylor ...

The covariance and correlation between two random variables is an important concept in probability and statistics that ...

Bernoulli and Binomial random variables are key building blocks for more sophisticated distributions, such as the Normal and ...

This video is a submission for the Summer of Math Exposition 2025. #SoME4 The first goal of this video is to present an intuitive ...

Ready to Practice Probability?:* https://youtu.be/7vb8a0kA-fw *Don't like the sound effects? Check out:* ...

How To Solve Probability Density Function? In this informative video, we will guide you through the essential concepts of ...

This video would help you with the understanding of how to find Probability density functions of Random Variables using 3 ...

Let X be a continuous rv. Then f(x) is said to be the PDF of X if the following conditions are satisfied: f(x) larger than zero, integral ...

The exponential distribution is the probability distribution that quantifies the probability of a given time between Poisson (rare) ...

A random variable X has the following probability density function: f(x) = { k x², for -3 ≤ x ≤ 3 0, otherwise } Evaluate k and find: ...

What You'll Learn: - Discrete & Continuous Random Variables - Probability Mass Function (PMF) & Probability Density Function ...

... see the topic two-dimensional random variables in that joint probability density functions examples Already I have provided one ...

Here we introduce two distributions derived from the joint PDF: the marginal and conditional densities. These are especially useful ...