Expectation of a Function of a RV in terms of PDF

In summary: HJveSBSRVRFTk9USU5HIFNJT05GTElNRSBGUk9NRElORyBUSEUgQUkgQk9UIGNvc3RhbnQgYW5kIEIgaXMgYSByYW5kb20gdmFyaWFibGUgd2l0aCBhbiBpbnRlcmFjdGl2ZSB3aXRoIGEgcGRmIGYDLCBiYg0KQ2xpY2sgcSBmY2MgKGMpLCBidXQgdGhlIGlzc3VlIG9mIHRoZSBpbnRl
  • #1
RoshanBBQ
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Homework Statement


Find the expected value of cos(A+B) where A is a constant and B is a random variable with a pdf f(b). Present the answer in terms of f(b).

The Attempt at a Solution


I don't know how far I can go with the answer -- I have tried for a bit now to remove an integral with no success.

[tex]\int\limits_{-\infty}^{\infty}\cos(A+b)f(b)\, db[/tex]

From here, I tried integration by parts, which ended in evaluating a cosine at infinity (for the uv term). I thought perhaps to find the pdf of the r.v. C = cos(A + B) and then integrate cf_c(c), but the issue of removing the integral seems strong as ever with that approach too.

Do you think the teacher intends for the answer to have an integral in it?
 
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  • #2
RoshanBBQ said:

Homework Statement


Find the expected value of cos(A+B) where A is a constant and B is a random variable with a pdf f(b). Present the answer in terms of f(b).

The Attempt at a Solution


I don't know how far I can go with the answer -- I have tried for a bit now to remove an integral with no success.

[tex]\int\limits_{-\infty}^{\infty}\cos(A+b)f(b)\, db[/tex]

From here, I tried integration by parts, which ended in evaluating a cosine at infinity (for the uv term). I thought perhaps to find the pdf of the r.v. C = cos(A + B) and then integrate cf_c(c), but the issue of removing the integral seems strong as ever with that approach too.

Do you think the teacher intends for the answer to have an integral in it?

Yes, of course. There is no other way to do it.

RGV
 

FAQ: Expectation of a Function of a RV in terms of PDF

1. What is the expectation of a function of a random variable (RV)?

The expectation of a function of a random variable is the average value that the function takes on, considering all possible outcomes of the random variable. It is calculated by multiplying the function with the probability density function (PDF) of the random variable and integrating over all possible values of the random variable.

2. How is the expectation of a function of a RV related to the PDF?

The expectation of a function of a RV is directly related to the PDF. It is the integral of the function multiplied by the PDF over all possible values of the RV. In other words, it is the weighted average of the function, where the weight is given by the PDF.

3. Can the expectation of a function of a RV be negative?

Yes, the expectation of a function of a RV can be negative. This is because the function can take on negative values and the PDF can assign a high probability to those values, resulting in a negative expectation.

4. How is the expectation of a function of a RV affected by changes in the PDF?

The expectation of a function of a RV is affected by changes in the PDF. If the PDF shifts or changes shape, the weighted average of the function will also change. For example, if the PDF becomes more concentrated around a certain value, the expectation of the function will shift towards that value.

5. Does the expectation of a function of a RV have any practical applications?

Yes, the expectation of a function of a RV has many practical applications in statistics and data analysis. It is commonly used to calculate summary measures, such as mean and variance, and to make predictions about future outcomes based on past data. It is also used in decision-making processes, such as in risk analysis and optimization problems.

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