Math Problem Statement

If 𝑋 X is a random variable with probability density function 𝑓 ( π‘₯ ) f(x), then the expected value of 𝑋 3 X 3 is given by:

A. 𝐸 ( 𝑋 3 )

∫ π‘₯ 3 / 2 𝑓 ( π‘₯ ) 𝑑 π‘₯ E(X 3 )=∫x 3/2 f(x)dx B. 𝐸 ( 𝑋 3 )

∫ π‘₯ 3 𝑓 ( π‘₯ ) 𝑑 π‘₯ E(X 3 )=∫x 3 f(x)dx C. 𝐸 ( 𝑋 3 )

∫ π‘₯ 6 𝑓 ( π‘₯ ) 𝑑 π‘₯ E(X 3 )=∫x 6 f(x)dx D. 𝐸 ( 𝑋 3 )

∫ π‘₯ 4 𝑓 ( π‘₯ ) 𝑑 π‘₯ E(X 3 )=∫x 4 f(x)dx

Solution

The expected value of X3X^3 for a random variable XX with probability density function f(x)f(x) is calculated using the definition of expected value:

E(X3)=∫x3f(x) dxE(X^3) = \int x^3 f(x) \, dx

This means we multiply the function x3x^3 by the probability density function f(x)f(x), and integrate over the range where f(x)f(x) is defined.

Thus, the correct answer is:

B. E(X3)=∫x3f(x) dxE(X^3) = \int x^3 f(x) \, dx

Let me know if you want a detailed breakdown or further questions!

5 Related Questions:

  1. What is the general formula for the expected value of XnX^n for any nn?
  2. How does the concept of expected value extend to discrete random variables?
  3. Can the expected value of X3X^3 be negative? Under what conditions?
  4. What is the difference between the expected value and the variance of a random variable?
  5. How do we calculate the expected value if the probability density function f(x)f(x) is piecewise?

Tip:

Always check that the probability density function f(x)f(x) satisfies the properties of being non-negative and integrates to 1 over its domain.

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Math Problem Analysis

Mathematical Concepts

Expected Value
Probability Density Function
Integration

Formulas

E(X^n) = ∫x^n f(x) dx

Theorems

Definition of Expected Value for Continuous Random Variables

Suitable Grade Level

Undergraduate - Probability and Statistics