![]() ![]() A random variable, usually denoted by X, Y, Z, X1, X2, Z3, etc., is actually a function! And like all well behaved functions, X has a domain and a range.ĭomain( X ): The domain of X is the sample space of random outcomes. The word ‘variable’ in random variable is a misnomer. Now that I have tickled your curiosity, let’s begin our journey into the wonderful world of Poisson processes.īut first, a quick overview of random variables and random processes. Pretty much any event that generates a sequence of whole numbered counts is a candidate for being modeled as a Poisson process. Number of meteors detected per hour during the Perseid meteor shower.Number of electrical pulses generated by a photo-detector that is exposed to a beam of photons, in 1 minute.The number of vehicles passing through some intersection from 8am to 11am on weekdays.Number of failures of ultrasound machines in a hospital over some period of time.The number of hot dogs sold by say, Papaya King, from 12pm to 4pm on Sundays. ![]() At a drive-through pharmacy, the number of cars driving up to the drop off window in some interval of time.Poisson processes can be seen in all walks of life. It turns out such “arrivals” data can be modeled very nicely using a Poisson process. While creating the above simulation, we have assumed that the average arrival rate is 5 patients per hour. The Y-axis shows the simulated time at which that patient arrived at a hospital’s Emergency Room. A sample Poisson process (Image by Author) ![]()
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |