In probability theory, a probability density function (pdf), or density of a continuous random variable, is a function that describes the relative likelihood for this random variable to take on a given value. The probability for the random variable to fall within a particular region is given by the integral of this variable’s density over the region. The probability density function is nonnegative everywhere, and its integral over the entire space is equal to one.
The terms "probability distribution function" and "probability function" have also sometimes been used to denote the probability density function. However, this use is not standard among probabilists and statisticians. In other sources, "probability distribution function" may be used when the probability distribution is defined as a function over general sets of values, or it may refer to the cumulative distribution function, or it may be a probability mass function rather than the density. Further confusion of terminology exists because density function has also been used for what is here called the "probability mass function".
Read more about Probability Density Function: Absolutely Continuous Univariate Distributions, Formal Definition, Further Details, Link Between Discrete and Continuous Distributions, Families of Densities, Densities Associated With Multiple Variables, Dependent Variables and Change of Variables, Sums of Independent Random Variables, Products and Quotients of Independent Random Variables
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