Poisson Distribution Explained
Poisson Distribution outputs the probability of a sequence of events happening in a fixed time interval.
Probability
Uniform Probability Distribution
In a Uniform Distribution Probability Density Function (PDF) is same for all the possible X values. Sometimes this is called a Rectangular Distribution. There are two (2) parameters in this distribution, a minimum (A) and a maximum (B)
Negative Binomial Distribution
In the Negative Binomial Distribution, we are interested in the number of Failures in n number of trials. This is why the prefix “Negative” is there. When we are interested only in finding number of trials that is required for a single success, we called it a Geometric Distribution.
Binomial Probability Distribution
Binomial Distribution is used to find probabilities related to Dichotomous Population. It can be applied to a Binomial Experiment where it can result in only two outcomes. Success or Failure. In Binomial Experiments, we are interested in the number of Successes.
Probability Mass Function
Probability Mass Function (PMF) of X says how the total probability of 1 is distributed (allocated to) among the various possible X values.
Expected Value of a Random Variable
Expected Value is the average value we get for a certain Random Variable when we repeat an experiment a large number of times. It is the theoretical mean of a Random Variable. Expected Value is based on population data. Therefore it is a parameter.