Density Function: A probability density function gives the probability of each possible outcome .

Distribution Function: A probability distribution function gives the probability of all possible outcomes accumulated from the reference outcome (starting point) up to the current outcome . The probability density function and the probability distribution function have the following relationship:

Discrete System	Continuous System

Mean Value: Mean Value, mean, or expectation, denoted by , is the likely outcome in an average sense. The average of all outcomes in a large-sample random sampling process is expected to be (close to) the mean value which is defined as:

Discrete System	Continuous System

Variance: Variance denoted by gives the spread of a distribution measured from the likely outcome . It is defined as:

Discrete System	Continuous System

Standard Deviation: Standard deviation, denoted by , is the positive square root of the variance. Both variance and standard deviation are used to describe the spread of a distribution.