Poisson Distribution

This distribution is based on the number of times the event occurs within a specific time period, such as the number of times the phone rings per minute or the number of errors per page of a document

overall, and that description is used in transport studies or in decid­ing upon the number of fuel stations to fuel cars, as well as in the design study for telephone lines.

Mean:

mt=A (3.22)

Standard Deviation:

tt = A (3.23)

It will be a probabilistic mass function, as shown in Figure (3.11) 5-Exponential Distribution

This distribution represents the time period between the occurrences of unanticipated events. For example, the time period between the occurrences of electronic failures in equipment reflects this distri­bution and is the opposite of Poisson distribution. It can be used to describe time periods to be expected between machine failures: there are now extensive studies that use this model to determine the appropriate time period for maintenance of equipment, called mean time between failure (MTBF).

x

Probability Density Function:

fT{t) = hTXt (3.24)

Mean:

Mt= 1/A (3.25)

Standard Deviation:

<7 = 1/A (3.26)