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3. Given that \[ f(x)=\left\{\begin{array}{cc}1 \sqrt{x}, & 0
Ask by Turner Pope. in the United States
Feb 20,2025

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Answer

\( k = \frac{3}{2} \) and \( P(0.3 < X < 0.6) \approx 0.289 \).

Solution

To solve the problem, we need to evaluate the constant \( k \) and then find the probability \( P(0.3 < X < 0.6) \) using the given density function. ### Part a: Evaluate \( k \) The function \( f(x) \) is defined as: \[ f(x) = \begin{cases} k \sqrt{x}, & 0 < x < 1 \\ 0, & \text{elsewhere} \end{cases} \] To find \( k \), we need to ensure that the total area under the probability density function (PDF) equals 1. This means we need to solve the following integral: \[ \int_{-\infty}^{\infty} f(x) \, dx = 1 \] Since \( f(x) = 0 \) outside the interval \( (0, 1) \), we can simplify the integral to: \[ \int_0^1 k \sqrt{x} \, dx = 1 \] Now, we will calculate the integral: \[ \int_0^1 \sqrt{x} \, dx \] The integral of \( \sqrt{x} \) can be computed as follows: \[ \int \sqrt{x} \, dx = \frac{2}{3} x^{3/2} \] Evaluating this from 0 to 1: \[ \left[ \frac{2}{3} x^{3/2} \right]_0^1 = \frac{2}{3} (1^{3/2} - 0^{3/2}) = \frac{2}{3} \] Now substituting back into the equation for \( k \): \[ k \cdot \frac{2}{3} = 1 \implies k = \frac{3}{2} \] ### Part b: Evaluate \( P(0.3 < X < 0.6) \) Now that we have \( k = \frac{3}{2} \), we can find the probability \( P(0.3 < X < 0.6) \): \[ P(0.3 < X < 0.6) = \int_{0.3}^{0.6} f(x) \, dx = \int_{0.3}^{0.6} \frac{3}{2} \sqrt{x} \, dx \] Calculating the integral: \[ \int \sqrt{x} \, dx = \frac{2}{3} x^{3/2} \] Now we evaluate this from 0.3 to 0.6: \[ \int_{0.3}^{0.6} \sqrt{x} \, dx = \left[ \frac{2}{3} x^{3/2} \right]_{0.3}^{0.6} \] Calculating the values: 1. For \( x = 0.6 \): \[ \frac{2}{3} (0.6)^{3/2} = \frac{2}{3} \cdot 0.6^{1.5} = \frac{2}{3} \cdot 0.4641 \approx 0.3081 \] 2. For \( x = 0.3 \): \[ \frac{2}{3} (0.3)^{3/2} = \frac{2}{3} \cdot 0.3^{1.5} = \frac{2}{3} \cdot 0.1732 \approx 0.1155 \] Now, substituting these values back into the integral: \[ \int_{0.3}^{0.6} \sqrt{x} \, dx \approx 0.3081 - 0.1155 = 0.1926 \] Finally, multiplying by \( \frac{3}{2} \): \[ P(0.3 < X < 0.6) = \frac{3}{2} \cdot 0.1926 \approx 0.289 \] ### Summary of Results a) \( k = \frac{3}{2} \) b) \( P(0.3 < X < 0.6) \approx 0.289 \)

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To evaluate the constant \( k \) in the probability density function \( f(x) \), we need to ensure that the total area under the curve equals 1. a) The function \( f(x) \) is defined as \( f(x) = \sqrt{x} \) for \( 0 < x < 1 \) and \( f(x) = 0 \) otherwise. Thus, we calculate: \[ \int_0^1 f(x) \, dx = \int_0^1 \sqrt{x} \, dx = \left[ \frac{2}{3} x^{3/2} \right]_0^1 = \frac{2}{3}(1^{3/2} - 0^{3/2}) = \frac{2}{3}. \] To normalize the density function, we set \( k \cdot \frac{2}{3} = 1 \), giving us \( k = \frac{3}{2} \). b) To find \( P(0.3 < X < 0.6) \), we compute: \[ P(0.3 < X < 0.6) = \int_{0.3}^{0.6} f(x) \, dx = \int_{0.3}^{0.6} \sqrt{x} \, dx. \] Calculating the integral, we have: \[ \left[ \frac{2}{3} x^{3/2} \right]_{0.3}^{0.6} = \frac{2}{3} (0.6^{3/2} - 0.3^{3/2}). \] Calculating \( 0.6^{3/2} = \sqrt{0.6^3} = \sqrt{0.216} \approx 0.464 \) and \( 0.3^{3/2} = \sqrt{0.3^3} = \sqrt{0.027} \approx 0.165 \): \[ P(0.3 < X < 0.6) \approx \frac{2}{3} (0.464 - 0.165) \approx \frac{2}{3} \times 0.299 \approx 0.199. \]

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