Select an arrival (Poisson) process on any time interval (eg.: second, minute, hour, day, week, month, etc….) as you like.
Possible arrival processes could be arrival of signal, click, broadcast, defective product, customer, passenger, patient, rain, storm, earthquake etc.[Hint: Poisson and exponential distributions exits at the same time.]
Collect approximately n=30 observations per unit time interval. .[Hint: Plot your observations. If there is sharp increase or decrease then you could assume that you are observing arrivals according to proper Poisson process. For example: when scheduled flight time approaches number of passengers arriving to the check-in increases. It is the same for arrival of students to the classroom]
Use this data to estimate λ of Poisson distribution. Estimate o λ denoted by =ΣXi/n (average of observations)
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