Engineering Analysis/Probability Functions
Probability Density Function[edit | edit source]
The probability density function, or pdf of a random variable is the function defined by:
Remember here that X is the random variable, and x is a related variable (but is not random). The subscript X on denotes that this is the pdf for the X variable.
pdf's follow a few simple rules:
- The pdf is always non-negative.
- The area under the pdf curve is 1.
Cumulative Distribution Function[edit | edit source]
The cumulative distribution function, (CDF), is also known as the Probability Distribution Function, (PDF). to reduce confusion with the pdf of a random variable, we will use the acronym CDF to denote this function. The CDF of a random variable is the function defined by:
The CDF and the pdf of a random variable are related:
The CDF is the function corresponding to the probability that a given value x is less than the value of the random variable X. The CDF is a non-decreasing function, and is always non-negative.
Example: X between two bounds[edit | edit source]
To determine whether our random variable X lies between two bounds, [a, b], we can take the CDF functions: