Question
3 points possible (graded)
Let X be an exponential random variable with parameter λ.
a) The probability that X > 5 is
b) The probability that X>5 given that X>2 is
c) Given that X>2 and for a small delta>0, the probability that 4<=X<=(4+2 delta) is approximately
Let X be an exponential random variable with parameter λ.
a) The probability that X > 5 is
b) The probability that X>5 given that X>2 is
c) Given that X>2 and for a small delta>0, the probability that 4<=X<=(4+2 delta) is approximately
Answers
Answered by
GPT-4o mini
Let \( X \) be an exponential random variable with parameter \( \lambda \). The probability density function (pdf) of \( X \) is given by:
\[
f_X(x) = \lambda e^{-\lambda x} \quad \text{for } x \geq 0
\]
The cumulative distribution function (CDF) is:
\[
F_X(x) = 1 - e^{-\lambda x} \quad \text{for } x \geq 0
\]
### a) The probability that \( X > 5 \)
The probability that \( X \) is greater than 5 is given by:
\[
P(X > 5) = 1 - F_X(5) = e^{-\lambda \cdot 5} = e^{-5\lambda}
\]
### b) The probability that \( X > 5 \) given that \( X > 2 \)
This can be calculated using the memoryless property of the exponential distribution. The memoryless property states that:
\[
P(X > s + t \mid X > s) = P(X > t)
\]
For \( s = 2 \) and \( t = 3 \) (since \( 5 - 2 = 3 \)):
\[
P(X > 5 \mid X > 2) = P(X > 3) = e^{-\lambda \cdot 3} = e^{-3\lambda}
\]
### c) Given that \( X > 2 \) and for a small \( \delta > 0 \), the probability that \( 4 \leq X \leq (4 + 2\delta) \) is approximately
For this case, we need the conditional probability \( P(4 \leq X \leq 4 + 2\delta \mid X > 2) \). We can use the definition of conditional probability:
\[
P(4 \leq X \leq 4 + 2\delta \mid X > 2) = \frac{P(4 \leq X \leq 4 + 2\delta)}{P(X > 2)}
\]
1. Calculate \( P(X > 2) \):
\[
P(X > 2) = e^{-2\lambda}
\]
2. Calculate \( P(4 \leq X \leq 4 + 2\delta) \):
\[
P(4 \leq X \leq 4 + 2\delta) = P(X \leq 4 + 2\delta) - P(X < 4) = (1 - e^{-\lambda(4+2\delta)}) - (1 - e^{-4\lambda}) = e^{-4\lambda} - e^{-\lambda(4+2\delta)}
\]
For small \( \delta \), we can use the approximation \( e^{-\lambda(4 + 2\delta)} \approx e^{-4\lambda} (1 - 2\delta\lambda) \):
\[
P(4 \leq X \leq 4 + 2\delta) \approx e^{-4\lambda} - e^{-4\lambda} (1 - 2\delta\lambda) = e^{-4\lambda} (2\delta\lambda)
\]
3. Now, substitute back into the conditional probability formula:
\[
P(4 \leq X \leq 4 + 2\delta \mid X > 2) = \frac{e^{-4\lambda} (2\delta\lambda)}{e^{-2\lambda}} = 2\delta\lambda e^{-2\lambda}
\]
Thus, given that \( X > 2 \) and for a small \( \delta > 0 \):
\[
P(4 \leq X \leq 4 + 2\delta \mid X > 2) \approx 2\delta\lambda e^{-2\lambda}
\]
\[
f_X(x) = \lambda e^{-\lambda x} \quad \text{for } x \geq 0
\]
The cumulative distribution function (CDF) is:
\[
F_X(x) = 1 - e^{-\lambda x} \quad \text{for } x \geq 0
\]
### a) The probability that \( X > 5 \)
The probability that \( X \) is greater than 5 is given by:
\[
P(X > 5) = 1 - F_X(5) = e^{-\lambda \cdot 5} = e^{-5\lambda}
\]
### b) The probability that \( X > 5 \) given that \( X > 2 \)
This can be calculated using the memoryless property of the exponential distribution. The memoryless property states that:
\[
P(X > s + t \mid X > s) = P(X > t)
\]
For \( s = 2 \) and \( t = 3 \) (since \( 5 - 2 = 3 \)):
\[
P(X > 5 \mid X > 2) = P(X > 3) = e^{-\lambda \cdot 3} = e^{-3\lambda}
\]
### c) Given that \( X > 2 \) and for a small \( \delta > 0 \), the probability that \( 4 \leq X \leq (4 + 2\delta) \) is approximately
For this case, we need the conditional probability \( P(4 \leq X \leq 4 + 2\delta \mid X > 2) \). We can use the definition of conditional probability:
\[
P(4 \leq X \leq 4 + 2\delta \mid X > 2) = \frac{P(4 \leq X \leq 4 + 2\delta)}{P(X > 2)}
\]
1. Calculate \( P(X > 2) \):
\[
P(X > 2) = e^{-2\lambda}
\]
2. Calculate \( P(4 \leq X \leq 4 + 2\delta) \):
\[
P(4 \leq X \leq 4 + 2\delta) = P(X \leq 4 + 2\delta) - P(X < 4) = (1 - e^{-\lambda(4+2\delta)}) - (1 - e^{-4\lambda}) = e^{-4\lambda} - e^{-\lambda(4+2\delta)}
\]
For small \( \delta \), we can use the approximation \( e^{-\lambda(4 + 2\delta)} \approx e^{-4\lambda} (1 - 2\delta\lambda) \):
\[
P(4 \leq X \leq 4 + 2\delta) \approx e^{-4\lambda} - e^{-4\lambda} (1 - 2\delta\lambda) = e^{-4\lambda} (2\delta\lambda)
\]
3. Now, substitute back into the conditional probability formula:
\[
P(4 \leq X \leq 4 + 2\delta \mid X > 2) = \frac{e^{-4\lambda} (2\delta\lambda)}{e^{-2\lambda}} = 2\delta\lambda e^{-2\lambda}
\]
Thus, given that \( X > 2 \) and for a small \( \delta > 0 \):
\[
P(4 \leq X \leq 4 + 2\delta \mid X > 2) \approx 2\delta\lambda e^{-2\lambda}
\]
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