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\( X \) is a normally distributed random variable with mean 48 and standard deviation 23 . What is the probability that \( X \) is between 2 and 71 ? Use the \( 0.68-0.95-0.997 \) rule and write your answer as a decimal. Round to the nearest thousandth if necessary.

Ask by Howell Floyd. in the United States
Jan 24,2025

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Answer

The probability that \( X \) is between 2 and 71 is approximately 0.815.

Solution

To determine the probability that \( X \) is between 2 and 71 using the \( 0.68-0.95-0.997 \) empirical rule, follow these steps: 1. **Identify the Mean and Standard Deviation:** - Mean (\( \mu \)) = 48 - Standard Deviation (\( \sigma \)) = 23 2. **Calculate the Z-scores for 2 and 71:** \[ z_1 = \frac{2 - 48}{23} = \frac{-46}{23} = -2 \] \[ z_2 = \frac{71 - 48}{23} = \frac{23}{23} = 1 \] 3. **Use the Empirical Rule:** - The empirical rule states: - Approximately 68% of data lies within \( \pm1\sigma \). - Approximately 95% within \( \pm2\sigma \). - Approximately 99.7% within \( \pm3\sigma \). - However, we're interested in \( P(-2 \leq Z \leq 1) \), which doesn't align perfectly with the standard intervals provided by the empirical rule. To approximate: - The interval \( -2\sigma \) to \( +2\sigma \) covers about 95%. - The interval \( -2\sigma \) to \( +1\sigma \) covers roughly 81.5%. 4. **Final Probability:** \[ P(2 \leq X \leq 71) \approx 0.815 \] **Rounded to the nearest thousandth, the probability is 0.815.** **Answer:** The probability is approximately 0.815

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To find the probability that \( X \) is between 2 and 71 in a normal distribution with mean \( \mu = 48 \) and standard deviation \( \sigma = 23 \), we can first standardize the values using the z-score formula: \[ z = \frac{(X - \mu)}{\sigma} \] For \( X = 2 \): \[ z_1 = \frac{(2 - 48)}{23} \approx -2 \] For \( X = 71 \): \[ z_2 = \frac{(71 - 48)}{23} \approx 1 \] Now we refer to the empirical rule: Approximately 68% of values lie within 1 standard deviation, 95% within 2 standard deviations, and 99.7% within 3 standard deviations of the mean. Since \( z_1 \) corresponds to roughly the -2 standard deviation mark and \( z_2 \) to the 1 standard deviation mark, the probability that \( X \) falls between these two z-scores can be calculated by determining the area under the normal curve from \( z = -2 \) to \( z = 1 \). This area represents: 1. Approximated by the empirical rule: About 95% of values lie within 2 standard deviations (\( -2 \) to \( 2 \)). 2. Since \( -2 \) to \( 0 \) is about 47.5% and \( 0 \) to \( 1 \) is about 34%, we're adding those portions: - From \( -2 \) to \( 0 \): 47.5% - From \( 0 \) to \( 1 \): 34% Adding these portions gives us: \[ P(2 < X < 71) \approx 47.5\% + 34\% = 81.5\% \] So as a decimal rounded to the nearest thousandth, the probability that \( X \) is between 2 and 71 is: \[ \text{Probability} \approx 0.815 \]

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