It relates to probability density functions by explaining how the distribution of these averages or sums tends to approach a specific shape: the normal distribution (bell curve).

6.2 The Normal Distribution (pp. 220-231) You are not required to memorize the formula for the normal probability density function, but rather know the properties (symmetry and bell shape).

The notion of probability density for a random function is not as straight-forward as in finite-dimensional cases. While a probability density function generally does not exist for functional data, we ...

An advantage of P-P plots is that they are discriminating in regions of high probability density, since in these regions the empirical and theoretical cumulative distributions change more rapidly than ...

Both normality and lognormality appear to be exceptions rather than the rule with respect to those distributions that may properly be inferred from the stochastic properties of the several series. The ...

Nonparametric method for multivariate density estimation using neural networks In this paper, a parameter-free method is proposed to determine the probability density function of multi-dimensional ...