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:
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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 largesample 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:
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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.
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Continuous System 


• For further details on the Probability Density Functions, Probability Distribution Functions, Mean Values, and Variances, please see the Distributions section.
