E[f(X)] - Expectation of function of rand. var.

In summary, the conversation discusses the expectation of a function of random variables, where the function is defined based on two disjoint conditions. It is clarified that independence is necessary for separating the expectations and the integration formula for finding the expectation is also mentioned.
  • #1
Apteronotus
202
0
Hi quick question:

Suppose you have a function of random variables given in the following way

Z=X if condition A
Z=Y if condition B

where both X and Y are random variables, and conditions A & B are disjoint.

Then would the expectation of Z be

E[Z]=E[X]*Pr(A)+E[Y]*Pr(B)?

Thanks in advance.
 
Last edited:
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  • #2
No you need independence for that, what you really mean is
[tex]Z=X\mathbf{1}_A+Y\mathbf{1}_B[/tex]
where 1 is the indicator function. Now take the expectation
[tex]\mathbb{E}[Z]=\mathbb{E}[X\mathbf{1}_A]+\mathbb{E}[Y\mathbf{1}_B] [/tex].

Now you know that [itex]\mathbb{E}[\mathbf{1}_A]=\mathbb{P}(A)[/itex], but to separate the expectations, you need independence between X and A, also between Y and B.
 
  • #3
Thank you Focus for your reply. I see my error.
 
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  • #4
You can use
[tex]\mathbb{E}[f(X)]=\int_{\mathbb{F}}f(x)F(dx)[/tex]
where F is the law of X. This may be somewhat abstract so if you are working over the reals and have a pdf f_X then
[tex]\mathbb{E}[f(X)]=\int_{\mathbb{R}}f(x)f_X(x)dx[/tex].
 

FAQ: E[f(X)] - Expectation of function of rand. var.

What is the definition of "E[f(X)]"?

E[f(X)] is the mathematical notation for the expectation of a function, where f(X) represents a function of a random variable X. It is a measure of the average value of the function over all possible outcomes of the random variable.

How is the expectation of a function of a random variable calculated?

The expectation of a function of a random variable is calculated by multiplying the function by the probability of each possible outcome of the random variable and then summing the results. This can be represented mathematically as E[f(X)] = ∑ f(x) * P(X=x), where x represents all possible values of the random variable X.

What is the significance of the expectation of a function of a random variable in statistics?

The expectation of a function of a random variable is an important concept in statistics as it allows us to calculate the average value of a certain function over all possible outcomes of a random variable. It is often used in probability theory and statistical analysis to make predictions and draw conclusions about a population.

Can the expectation of a function of a random variable be negative?

Yes, the expectation of a function of a random variable can be negative. This means that the average value of the function over all possible outcomes of the random variable is below zero. It is important to note that the expectation of a function of a random variable is not limited to positive values only.

How does the expectation of a function of a random variable differ from the expectation of a random variable?

The expectation of a random variable represents the average value of the random variable itself, while the expectation of a function of a random variable represents the average value of a function that is applied to the random variable. In other words, the expectation of a function of a random variable takes into account the effect of the function on the random variable's values, rather than just the values themselves.

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