Formula for the expected value of a function

In summary, the formula for the expected value of a continuous random variable does not apply to functions of random variables. The correct formula for the expected value of a function g(x) is E(x) = \int_{-\infty}^{\infty} g(x)\cdot f(x).
  • #1
gsingh2011
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1
The formula for the expected value of a continuous random variable is [itex]E(x) = \int_{-\infty}^{\infty} x\cdot f(x)[/itex]. This leads me to believe that the expected value of a function g(x) is [itex]E(x) = \int_{-\infty}^{\infty} g(x)\cdot f(g(x))[/itex]. However, the correct formula is [itex]E(x) = \int_{-\infty}^{\infty} g(x)\cdot f(x)[/itex]. Why is this?
 
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  • #2
You're talking about a "function of a random variable" (which is itself a random variable) not an ordinary function. The definition of the expectation of a random variable involves an integrand that is the product of the value of the variable times the probability density of the random variable evaluated at that value. If X is a random varaible with density f(x) and Y = g(X) is a function of the random variable X then it is not generally true that the probability density of Y is f(g(x)). Hence f(g(x)) is not the appropriate term to use in the integrand when computing the expectation of Y.
 

FAQ: Formula for the expected value of a function

What is the formula for the expected value of a function?

The formula for the expected value of a function is E[f(x)] = ∑f(x)*P(x), where f(x) is the function, P(x) is the probability of x occurring, and ∑ is the summation symbol.

How is the expected value of a function calculated?

The expected value of a function is calculated by multiplying the function by its respective probabilities and summing them up.

What is the significance of the expected value of a function in statistics?

The expected value of a function is an important concept in statistics as it represents the average value of a random variable or process. It can be used to make predictions and inform decision making.

What is the difference between expected value and actual value?

The expected value of a function is a theoretical value based on probabilities, while the actual value is the observed or measured value in a specific instance. The expected value may or may not match the actual value.

Can the expected value of a function be negative?

Yes, the expected value of a function can be negative. This is possible when the function has a mix of positive and negative values and their respective probabilities result in a negative overall value.

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