Conditional Expectations

A conditional expectation is the estimated outcome of an event given expectations of another event. The math notation is E[X|Y].


Evaluation

For a discrete distribution, a conditional expectation is generally expanded as Σ E[X|Y=y] p(Y=y) (for all Y=y).

For a continuous distribution, a conditional expectation is generally expanded as ∫ E[X|Y=y] p(Y=y) dx (for all Y=y).

Then continue to evaluate the expected values of X given Y=y.

Bernoulli

Bernoulli-distributed variables have some useful properties.

Given a Bernoulli-distributed X, for the same reason that E[X] = p(X=1) (i.e. the 0 term eliminates itself), it is also true that E[X|Y] = E[X=1|Y].

Given Bernoulli-distributed X and Y, E[X|Y] can be evaluated by the above general expansion.

expansion.svg

But a more useful rewrite is E[X|Y] = p(X|Y). Then continue to evaluate the conditional probabilities of X given Y.


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Statistics/ConditionalExpectations (last edited 2024-03-21 20:44:18 by DominicRicottone)