### What is Bayesian Statistics? Can you explain it to a layman

What is Bayesian Statistics: (I will try to explain in easy
terms)

Often researchers investigating an unknown population
parameter have information available from other sources in advance of the study
that provides a strong indication of what values the parameter is likely to
take. This additional information might be in a form that cannot be
incorporated directly in the current study. The classical statistical approach
offers no scope for the researchers to take this additional information into
account. However, the Bayesian statistics is the approach which allows to take
this additional information into account while estimating a population parameter.

Let me explain you with the help of an example:

4 championship races had been done between Mr. A and Mr. B.
Out of which A has won 3 races and B has won 1 race. SO, on whom are you going
to bet your money in the next race?

You will Say Mr. A because P(A) = 0.75 and P(B) = 0.25

So your initial estimate about B is P(B) = 0.25

So your initial estimate about B is P(B) = 0.25

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Now I will give you additional information say, there was a
rain when Mr. B won and there was rain once when Mr. A won. And in the next match
there will definitely be a rain.

So now I ask you again on whom will you bet your money?

So now I ask you again on whom will you bet your money?

Let’s decode the answer:

1. P(R) = 0.50 (Because rain happened twice out of 4 matches)

2. P(R|B) = 1 (Because whenever Mr. B won there was a rain)

1. P(R) = 0.50 (Because rain happened twice out of 4 matches)

2. P(R|B) = 1 (Because whenever Mr. B won there was a rain)

So I want to find out that what is probability that in the
next race Mr. B will won if it is given that there will be a rain:

P(B|R) = P(R|B)*P(B)/P(R) = 0.50

I hope you know how this formula comes up otherwise you can mention me in comments I will tell you how.

I hope you know how this formula comes up otherwise you can mention me in comments I will tell you how.

Conclusion: Initially we comes up with an answer that P(B) =
0.25 which is my prior estimate and then I give additional information about
rain which we incorporated in the form of conditional probability i.e. P(R|B) =
1 and then ultimately we find P(B|R) which is my posterior probability.

So you see how with the help of Bayesian statistics I incorporated additional information into my current study and how my value changes from 0.25 to 0.50.

So you see how with the help of Bayesian statistics I incorporated additional information into my current study and how my value changes from 0.25 to 0.50.

Statistics seems easy now. ðŸ˜Š

Its an art and you are an artist.

Its an art and you are an artist.

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**Follow me on LinkedIn: Kamal Sardana**

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