There are frequently situations where you have information on the conditional distribution of Y given X, but are interested in the conditional distribution of X given Y. Recalling Pr(Y = y $\mid X$ = x)= $\frac { \operatorname { Pr } ( X = x , Y = y ) } { \operatorname { Pr } ( X = x ) }$ , derive a relationship between Pr(X = x $\mid Y$ = y)and Pr(Y = y $\mid X$ = x). This is called Bayes' theorem.

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The Answer of There are frequently situations where you have information on the conditional distribution of Y given X, but are interested in the conditional distribution of X given Y. Recalling Pr(Y = y $\mid X$ = x)= $\frac { \operatorname { Pr } ( X = x , Y = y ) } { \operatorname { Pr } ( X = x ) }$ , derive a relationship between Pr(X = x $\mid Y$ = y)and Pr(Y = y $\mid X$ = x). This is called Bayes' theorem.

There Are Frequently Situations Where You Have Information on the Conditional