The probability density function measures continuous variables. Having said that, it's important to note that stock and investment returns are generally not continuous random variables.

Probability distributions are characterized as either discrete or continuous, and as working as either a probability density function, or a cumulative distribution.

Let x1, ⋯, xn be independent observations on a p-dimensional random variable X = (X1, ⋯, Xp) with absolutely continuous distribution function F (x1, ⋯, xp). An observation xi on X is xi = (x1i, ⋯, xpi ...

CIVE.2860 — Undergraduate Id: 002972 Offering: 1 Credits: 3-3 Description Probability, statistics, reliability and decision with applications in engineering. Probability of events, discrete and ...

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model.

Let x and y be two random variables with continuous cumulative distribution functions f and g. A statistic U depending on the relative ranks of the x's and y's is proposed for testing the hypothesis f ...