Comprehension

Let \( X \) denote the number of hours a Class 12 student studies during a randomly selected school day. The probability that \( X \) can take the values \( x_i \), for an unknown constant \( k \):

\[ P(X = x_i) = \begin{cases} 0.1, & {if } x_i = 0, \\ kx_i, & {if } x_i = 1 { or } 2, \\ k(5 - x_i), & {if } x_i = 3 { or } 4. \end{cases} \]

Question: 1

Find the value of \( k \).

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In probability distributions, the sum of all probabilities must be equal to 1. Use this property to find unknown parameters.
Updated On: Feb 11, 2025
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Solution and Explanation

Step 1: The total probability must sum to 1: \[ P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) = 1. \] Step 2: Substitute the given probability values: \[ P(X = 0) = 0.1, \quad P(X = 1) = k(1), \quad P(X = 2) = k(2), \] \[ P(X = 3) = k(5 - 3), \quad P(X = 4) = k(5 - 4). \] Step 3: Form the equation: \[ 0.1 + k(1) + k(2) + k(2) + k(1) = 1. \] Step 4: Simplify the equation: \[ 0.1 + 6k = 1. \] Step 5: Solve for \( k \): \[ k = \frac{1 - 0.1}{6} = \frac{0.9}{6} = 0.15. \]
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Question: 2

Determine the probability that the student studied for at least 2 hours.

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For cumulative probability calculations, sum up the probabilities of all values greater than or equal to the given threshold.
Updated On: Feb 11, 2025
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Solution and Explanation

Step 1: The probability of the student studying for at least 2 hours is given by: \[ P(X \geq 2) = P(X = 2) + P(X = 3) + P(X = 4). \] Step 2: Substitute the values from the given probability distribution: \[ P(X \geq 2) = k(2) + k(5 - 3) + k(5 - 4). \] Step 3: Substitute \( k = 0.15 \): \[ P(X \geq 2) = 0.15(2) + 0.15(2) + 0.15(1). \] Step 4: Compute the value: \[ P(X \geq 2) = 0.3 + 0.3 + 0.15 = 0.75. \] Thus, the probability that the student studied for at least 2 hours is **0.75**.
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Question: 3

Determine the probability that the student studied for at most 2 hours.

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For cumulative probability calculations, sum up the probabilities of all values less than or equal to the given threshold.
Updated On: Feb 11, 2025
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Solution and Explanation

Step 1: The probability that the student studied for at most 2 hours is given by: \[ P(X \leq 2) = P(X = 0) + P(X = 1) + P(X = 2). \] Step 2: Substitute the given values: \[ P(X \leq 2) = 0.1 + k(1) + k(2). \] Step 3: Substitute \( k = 0.15 \): \[ P(X \leq 2) = 0.1 + 0.15(1) + 0.15(2). \] Step 4: Compute the value: \[ P(X \leq 2) = 0.1 + 0.15 + 0.3 = 0.55. \] Thus, the probability that the student studied for at most 2 hours is 0.55.

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Question: 4

A river near a small town floods and overflows twice in every 10 years on an average. Assuming that the Poisson distribution is appropriate, what is the mean expectation? Also, calculate the probability of 3 or less overflows and floods in a 10-year interval.
[Given \( e^{-2} = 0.13534 \)]

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For Poisson distribution problems, use the formula \( P(X = k) = \frac{\lambda^k e^{-\lambda}}{k!} \). To calculate \( P(X \leq k) \), sum the probabilities from \( P(X = 0) \) to \( P(X = k) \).
Updated On: Feb 11, 2025
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Solution and Explanation

Step 1: The Poisson distribution formula is: \[ P(X = k) = \frac{\lambda^k e^{-\lambda}}{k!}, \] where \( \lambda \) is the average rate of occurrence, \( k \) is the number of occurrences, and \( e \) is the base of the natural logarithm. 
Step 2: Mean expectation (\( \lambda \)): The average number of floods in 10 years is \( \lambda = 2 \). 
Step 3: Probability of 3 or fewer overflows (\( P(X \leq 3) \)): \[ P(X \leq 3) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3). \] Using the Poisson formula: - For \( P(X = 0) \): \[ P(X = 0) = \frac{2^0 e^{-2}}{0!} = \frac{1 \cdot 0.13534}{1} = 0.13534. \] - For \( P(X = 1) \): \[ P(X = 1) = \frac{2^1 e^{-2}}{1!} = \frac{2 \cdot 0.13534}{1} = 0.27068. \] - For \( P(X = 2) \): \[ P(X = 2) = \frac{2^2 e^{-2}}{2!} = \frac{4 \cdot 0.13534}{2} = 0.27068. \] - For \( P(X = 3) \): \[ P(X = 3) = \frac{2^3 e^{-2}}{3!} = \frac{8 \cdot 0.13534}{6} = 0.18045. \] 
Step 4: Add the probabilities: \[ P(X \leq 3) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3). \] Substitute the values: \[ P(X \leq 3) = 0.13534 + 0.27068 + 0.27068 + 0.18045 = 0.85715. \] 
Final Answers: - Mean expectation: \( \lambda = 2 \). - Probability of 3 or fewer overflows: \( P(X \leq 3) = 0.85715 \) or approximately \( 85.72\% \).

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