2. Answer the following questions. A random variable \( X \) has a mean 8 , a variance 9 , and an unknown probability distribution. Using Chebyshev's theorem, find the lower bound of \( P(|X-8| \geq 6) \).
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Chebyshev's theorem tells us that for any random variable, the proportion of observations that lie within \( k \) standard deviations of the mean is at least \( 1 - \frac{1}{k^2} \). In this case, the mean \( \mu = 8 \) and the variance \( \sigma^2 = 9 \), so the standard deviation \( \sigma = 3 \). To find \( P(|X - 8| \geq 6) \), we consider \( |X - 8| \geq 6 \) which is equivalent to \( |X - 8| < 6 \). Here, we define \( k \) as the number of standard deviations: \( k = \frac{6}{3} = 2 \). Now applying Chebyshev's theorem: \[ P(|X - 8| < 6) \geq 1 - \frac{1}{k^2} = 1 - \frac{1}{2^2} = 1 - \frac{1}{4} = \frac{3}{4}. \] Thus, the probability of being outside that range is: \[ P(|X - 8| \geq 6) \leq 1 - P(|X - 8| < 6) \leq 1 - \frac{3}{4} = \frac{1}{4}. \] So, the lower bound of \( P(|X - 8| \geq 6) \) is at least \( \frac{1}{4} \).