3. Let X denote the temperature at which a certain chemical reaction takes place. Suppose that X has pdf: f(x) Find the expected value E(2X). 9 (4- x²), -1 < x < 2

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### Problem 3: Expected Value of a Random Variable

**Problem Statement:**

Let \( X \) denote the temperature at which a certain chemical reaction takes place. Suppose that \( X \) has the probability density function (pdf):
\[ f(x) = \frac{1}{9}(4 - x^2), \quad -1 < x < 2 \]

Find the expected value \( E(2X) \).

**Solution Process:**
1. **Understanding the Probability Density Function (pdf):**
   - The given pdf is \( f(x) = \frac{1}{9}(4 - x^2) \) which is valid within the interval \( -1 < x < 2 \).
   - This pdf describes the probability distribution of the random variable \( X \).

2. **Expected Value of 2X:**
   - The expected value \( E(aX) \) of a random variable for a constant \( a \) is given by \( aE(X) \).
   - Hence, \( E(2X) = 2E(X) \).

3. **Compute \( E(X) \):**
   - The expected value \( E(X) \) for a continuous random variable with pdf \( f(x) \) is calculated by:
     \[ E(X) = \int_{-\infty}^{\infty} x f(x) \, dx \]
   - Given our interval, it becomes:
     \[ E(X) = \int_{-1}^{2} x f(x) \, dx \]
   - Substituting the pdf:
     \[ E(X) = \int_{-1}^{2} x \cdot \frac{1}{9}(4 - x^2) \, dx \]
   - Simplifying and solving this integral will give you \( E(X) \).

   **Explanation of the Diagram:**
   - If there were a graph, it would typically illustrate the pdf \( f(x) \) (a parabola opening downwards) between \( x = -1 \) and \( x = 2 \).
   - The area under this curve from \( x = -1 \) to \( x = 2 \) would represent the total probability, which is 1.

4. **Final Calculation:**
   - Once \( E(X) \) is computed, multiply this result by 2 to find
Transcribed Image Text:### Problem 3: Expected Value of a Random Variable **Problem Statement:** Let \( X \) denote the temperature at which a certain chemical reaction takes place. Suppose that \( X \) has the probability density function (pdf): \[ f(x) = \frac{1}{9}(4 - x^2), \quad -1 < x < 2 \] Find the expected value \( E(2X) \). **Solution Process:** 1. **Understanding the Probability Density Function (pdf):** - The given pdf is \( f(x) = \frac{1}{9}(4 - x^2) \) which is valid within the interval \( -1 < x < 2 \). - This pdf describes the probability distribution of the random variable \( X \). 2. **Expected Value of 2X:** - The expected value \( E(aX) \) of a random variable for a constant \( a \) is given by \( aE(X) \). - Hence, \( E(2X) = 2E(X) \). 3. **Compute \( E(X) \):** - The expected value \( E(X) \) for a continuous random variable with pdf \( f(x) \) is calculated by: \[ E(X) = \int_{-\infty}^{\infty} x f(x) \, dx \] - Given our interval, it becomes: \[ E(X) = \int_{-1}^{2} x f(x) \, dx \] - Substituting the pdf: \[ E(X) = \int_{-1}^{2} x \cdot \frac{1}{9}(4 - x^2) \, dx \] - Simplifying and solving this integral will give you \( E(X) \). **Explanation of the Diagram:** - If there were a graph, it would typically illustrate the pdf \( f(x) \) (a parabola opening downwards) between \( x = -1 \) and \( x = 2 \). - The area under this curve from \( x = -1 \) to \( x = 2 \) would represent the total probability, which is 1. 4. **Final Calculation:** - Once \( E(X) \) is computed, multiply this result by 2 to find
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