Cumulative distribution function

In probability theory, a cumulative distribution function F(x) of a probability density function say f(x) is a real valued and continuous function whose value is the proportion of probability values of a variable which occur on the part real line up and including the value of that variable; i.e.,

$F(x)=\int _{-\infty }^{x}\,f(\lambda )\,d\lambda$

Due to the properties of the probability density function f(x), the cumulative distribution function F(x) will have the following properties:

(1) $F(x)\geq 0$ $\forall x$ inside its domain of support.

(2) $F(\infty )=1$, i.e., finitely convergent (to unity by convention).

(3) $F(a)\leq F(b)$ for a<b, i.e., is non-decreasing

If the domain of the variable is finite, then the argument in equation (2) above should be the upper bounds.