Expectation of probability density function

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Discussion Overview

The discussion revolves around the expectation of a probability density function (pdf) and the generalization of the expected value to functions of random variables. Participants explore the calculation of expected values using different methods and address discrepancies in results.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Some participants propose that the expected value E(X) of a probability density function f(x) is defined as the integral \int x f(x) dx.
  • Others suggest that E(g(x)) can be generalized to E(g(x)) = \int g(x) f(x) dx, treating it as a definition of expected value for any function g(x).
  • One participant describes two methods to calculate E(5 + 10X) and notes that they obtained different results, raising a question about which method is correct.
  • Another participant asserts that both methods are correct, implying a mistake was made in the integration process.
  • A later reply indicates that the participant who questioned their results may have misphrased their question, suggesting a potential misunderstanding rather than a mathematical error.

Areas of Agreement / Disagreement

Participants generally agree on the definitions of expected values and the generalization to functions of random variables. However, there is disagreement regarding the correctness of the different methods used to calculate E(5 + 10X), as one participant believes they obtained different answers while others assert both methods are valid.

Contextual Notes

There are indications of potential misunderstandings in the integration process, but specific details about the nature of the mistakes or assumptions involved are not fully resolved.

songoku
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E(X) of probability density function f(x) is \int x f(x) dx

E(X2) of probability density function f(x) is \int x^2 f(x) dx

Can I generalize it to E(g(x)) of probability density function f(x) = \int g(x). f(x) dx ?

I tried to find E(5 + 10X) from pdf. I did two ways:
1. I found E(X) then using linear combination of random variable, E (5 + 10X) = 5 + 10 E(X)

2. Using integration, \int (5 + 10x) f(x) dx

I got two different answers. Which one is correct and why?

Thanks
 
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songoku said:
E(X) of probability density function f(x) is \int x f(x) dx

E(X2) of probability density function f(x) is \int x^2 f(x) dx

Can I generalize it to E(g(x)) of probability density function f(x) = \int g(x). f(x) dx ?

I tried to find E(5 + 10X) from pdf. I did two ways:
1. I found E(X) then using linear combination of random variable, E (5 + 10X) = 5 + 10 E(X)

2. Using integration, \int (5 + 10x) f(x) dx

I got two different answers. Which one is correct and why?

Thanks

They are both correct. You must have made a mistake integrating.
 
songoku said:
E(X) of probability density function f(x) is \int x f(x) dx

E(X2) of probability density function f(x) is \int x^2 f(x) dx

Can I generalize it to E(g(x)) of probability density function f(x) = \int g(x). f(x) dx ?

Yes. In fact, you could take that to be the definition of the expected value of some function ##g(x)##. Then, ##E(x)## and ##E(x^2)## are specific cases of ##g(x)##.
 
I re-checked so many times and apparently the mistake was I wrote the question wrongly o:)

Thank you so much perok
 
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