The continuous probability distribution describing the time until the failure of a component if the probability of a failure does not change with the component's age
Probably the most widely known and used distribution in reliability evaluation of systems The most important factor for it to be applicable is that the hazard rate should be constant Exponential distribution is frequently used for the analysis of time-dependent data when the rate at which events occur does not vary
A continuous probability distribution useful for characterizing random variables which may only take positive values It is often used to characterize the time between events such as arrivals of customers at a store The distribution is completely determined by its mean For the exponential distribution, the mean and standard deviation are equal It is highly skewed to the right, peaking at zero and decaying in a smooth (exponential) fashion Parameter: mean B>0 Domain: X>=0 Mean: B Variance: B^2
The exponential distribution very often works well for modeling processes involving time intervals between events and sometimes for durations of activities For modeling the arrivals of customers, parts, or other entities that come into a system from a large number of different independent sources, the exponential distribution is often a good choice for the distribution of the random variable representing the time between consecutive arrivals ( i e , the interarrival time) The distribution function can be expressed as follows