The Multinomial Distribution : Data Science Basics 

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the process comes from stochastic modeling. You can use gamma distribution as a way to generalize exponential distribution. Exponential distribution models the time between events which belong to a Poisson process. the gamma distribution models the time between Poisson process but u can have it model a particular trial. If you have a Poisson process with a rate of 2 events per hour, the time until the 3rd event follows a gamma distribution with shape parameter 3 and rate parameter 2. This means the waiting time until the 3rd event is the sum of three independent exponential random variables, each with a mean of 0.5 hours. With regards to bayesian statistics, we use the gamma distribution as an a priori to adjust parameters in a Poisson process. We can use gamma as a conjugate prior for Poisson likelihood. I suggest taking a course in stochastic models to learn more about this distribution, as that is where u can see a large amount of applications.

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please start your channel! there's tons of videos on RU-vid about the same topic; different people learn differently so you'll definitely be adding to the community

@@ritvikmath I agree. Sometimes you’re might get things from explanation in other videos things faster.

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