probability density function
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A probability density function is a mathematical tool that describes how likely different outcomes are in a situation where results can vary continuously (like measuring height or temperature). It matters because by calculating the area under this function across any range of values, you can determine the probability that an outcome will fall within that range.
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Box plot and probability density function of a normal distribution N(0, σ). Geometric visualisation of the mode, median and mean of an arbitrary unimodal probability density function.
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.