The Probability Density Function (PDF) Introduction So far, you learned about discrete random variables and how to calculate or visualize their distribution functions. In this lesson, you'll learn ...

The next statement shows how to compute the probability that continuous random variable X with pdf f (x) lies in the interval [a,b]. The cumulative density function (cdf) for random variable X with ...

Adding probabilities across the rows you get the probability distribution of random variable X (called the marginal distribution of X). Adding probabilities down the columns you get the probability ...

A random variable that counts the number of 1's in 18 dice rolls is similar to one that counts the number of heads in 100 coin tosses or the number of females in 50 births. The probability functions ...

Using Equation (5), for any continuous random variable X on R, we can define a discrete random variable Y that has integer support on Z. When the skew Laplace density (6) where, , are inserted into ...

For this reason, we cannot build a probability function same way as we did for the discrete variables. Instead, we are using the probability density function which allows us to evaluate probability of ...

To construct a method for estimating finite-discrete-probability distributions of random variable X from sample set of finite size n, the following quantities are defined. denotes a ...

Jensen gave a lower bound to Eρ (T), where ρ is a convex function of the random vector T. Madansky has obtained an upper bound via the theory of moment spaces of multivariate distributions. In ...