A probability distribution is a table or an equation that links each outcome of a statistical experiment with its probability of occurrence.
It defines what will be the probability of an event to take place and how common are the values in a given range.
Example 1 :- Suppose we flip a coin ,the probability of Head and Tail is 0.5 and 0.5 respectively.
This can considered as the simplest probability distribution.
Example 2:- Suppose we flip two coin and we need to find the probability of occurrence of head in each coin.
probability of 0 head ---->0.25
probability of 1 head ---->0.50
probabilty of 2 head ---->0.25
So, the above table represents our probabilty distribution.
Probability Distribution are commonly classified into two parts:-
1.) Continuous , data can take any value within a specified range.
2.) Discrete , data can take only certain values.
1.) The probabilities must lie in between 0 and 1 .
2.) The sum of all the probabilities must equal to 1.
It defines what will be the probability of an event to take place and how common are the values in a given range.
Example 1 :- Suppose we flip a coin ,the probability of Head and Tail is 0.5 and 0.5 respectively.
This can considered as the simplest probability distribution.
Example 2:- Suppose we flip two coin and we need to find the probability of occurrence of head in each coin.
probability of 0 head ---->0.25
probability of 1 head ---->0.50
probabilty of 2 head ---->0.25
So, the above table represents our probabilty distribution.
Probability Distribution are commonly classified into two parts:-
1.) Continuous , data can take any value within a specified range.
2.) Discrete , data can take only certain values.
Rules which make the probability Distribution Valid:-
1.) The probabilities must lie in between 0 and 1 .
2.) The sum of all the probabilities must equal to 1.
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