The Poisson is a classic distribution used in operational risk. It often fits (describes) random variables over time intervals. For example, it might try to characterize the number of low severity, high frequency (HFLS) loss events over a month or a year. It is a discrete function that conveniently only needs one parameter: lambda, which is both the mean and the variance.
Incredibly helpful video! Thanks for your time!
UseLogicPlease123 4 months ago
@faYte0607 lamda = n * p
n=100
p=0.05
tdkyun 8 months ago
Thanks very much for an excellent explanation. Really helpful.
ManLondon 9 months ago
You should really explain how you got the lamda number 5 in the first problem...
faYte0607 1 year ago
your explanation made me so confortable for this distriibution.
hirokame2009 1 year ago
Best explain had ! Thanks
pavljiks13 1 year ago
You are amazing. I wish you were my Professor.
Squidzu 2 years ago
im not exactly sure. its about the scope of the values you have. i think if its a number of events PER greater event, you use the poisson. like number of typos PER page in a book. or number of craters PER square mile of the moon. or number of car accidents PER road in manhattan.
LucaToniIsMeinPapa 2 years ago
Hey, I just wanted to know when I should use the Poisson, and when I should use the Counting Rules for Combination? Or are they the same?
I found that they give about the same value: though I could be doing them both wrong.
Does anyone know?
EntreMind 2 years ago
Given that we're examining 100 objects it wouldn't be .05 of those. It would be 5.
CaptainCrunchOwns 2 years ago