Editing Examples of Markov chains (section)

== Continuous-time ==

=== A birth–death process ===
{{See also|Birth–death process|Poisson point process}}If one pops one hundred kernels of popcorn in an oven, each kernel popping at an independent [[Exponential distribution|exponentially-distributed]] time, then this would be a [[continuous-time Markov process]]. If <math>X_t</math> denotes the number of kernels which have popped up to time ''t'', the problem can be defined as finding the number of kernels that will pop in some later time. The only thing one needs to know is the number of kernels that have popped prior to the time "t". It is not necessary to know ''when'' they popped, so knowing <math>X_t</math> for previous times "t" is not relevant.

The process described here is an approximation of a [[Poisson point process]] – Poisson processes are also Markov processes.