STATISTICS FOR DATA ANALYTICS - 9
Discrete probability distribution : - Pmf ( Probability Mass Function )
Types :-
Bernoulli distribution
Discrete random variable
Outcome is binary.
It is generated when we perform an experiment once and it has only two possible outcomes - success or failure.
0<= p<=1
q=1-p
K{ success, fail } = 0, 1
Eg :- toss, rain.
Binomial distribution
Discrete random variable
Outcome is binary but it has multiple cases.
This distribution is generated when we perform an experiment repeatedly n times and plot the probability each time.
Eg :- 5 balls in a bag ( 3 red and 2 black ) probability with binomial we can get values without calculating the values.
Condition for binomial distribution :-
Each trial is independent since the outcome of the previous toss doesn't determine or affect the outcome of the current toss.
Bernoulli distribution is a special case of the binomial distribution case.
Poisson distribution ..
Discrete random variable
Outcome is binary but it has multiple cases.
With this distribution, We can estimate the average number values but not the time and values, it also describe the no.of event occuring in a fixed interval of time.
Estimate value is also called lambda.
Eg :- no.of people visiting any specific place.
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