
Probability density function
Description of continuous random distribution

Description of continuous random distribution
In probability theory, a probability density function (PDF), density function, or simply density of an absolutely continuous random variable, is a function whose value at any given point in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a "relative probability" that the value of the random variable would be equal to that point. Probability density is the probability per unit length, in other words. The (absolute) probability for a continuous random variable to take on any particular value is zero. Therefore, the value of the PDF at two different samples can be used to infer, in any particular draw of the random variable, how much more likely it is that the random variable would be close to one point compared to the other. More precisely, the PDF is used to specify the probability of the random variable falling within a particular range of values, as opposed to taking on any one value. This probability is given by the integral of...
Read on Wikipedia · Image Original uploader was Jhguch at en.wikipedia; Derivative work: Chen-Pan Liao (talk)., CC BY-SA 2.5
Open boosters, collect cards and trade them. Free to play.
Play for free