It is the integral (or sum) of the joint probability distribution function of the two events, integrated over the domain in which the condition is met.
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The derivative of the moment generating function is the expectation. The variance is the second derivative of the moment generation, E(x^2), minus the expectation squared, (E(x))^2. ie var(x)=E(x^2)-(E(x))^2 :)
A conditional statement uses the words if... Then
To remove the condition from conditional asymptotic notation, you can express the function in terms of a simpler function that captures its growth rate without additional constraints. For example, if you have a function ( f(n) ) that is ( O(g(n)) ) under certain conditions, you can analyze its behavior in a broader context or identify a dominant term that represents its growth more generally. This often involves finding bounds that apply universally or altering the function to eliminate dependencies on specific conditions. Ultimately, the goal is to represent the function's asymptotic behavior in a more straightforward manner.
I assume this is a trick question, and the answer is "everything". If you expect it, it is your expectation and if it is your expectation, you expect it.
If you mean probabilistic expectation, the answer is no.