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\( X \) is a normally distributed random variable with mean 73 and standard deviation 18 . What is the probability that \( X \) is less than 55 ? 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 Pope Mullins. in the United States
Jan 24,2025

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Answer

The probability that \( X \) is less than 55 is **0.16**.

Solution

To determine the probability that \( X \) is less than 55, given that \( X \) is normally distributed with a mean (\( \mu \)) of 73 and a standard deviation (\( \sigma \)) of 18, we can use the **68-95-99.7 rule**. This rule provides a quick way to estimate probabilities for normally distributed data based on standard deviations from the mean. ### Step-by-Step Solution: 1. **Calculate the Z-score:** \[ Z = \frac{X - \mu}{\sigma} = \frac{55 - 73}{18} = \frac{-18}{18} = -1 \] A Z-score of -1 indicates that 55 is one standard deviation below the mean. 2. **Apply the 68-95-99.7 Rule:** - **68%** of the data falls within ±1 standard deviation from the mean. - Therefore, **32%** of the data falls outside this range (100% - 68%). - Since the normal distribution is symmetric, half of this 32% lies below \( \mu - 1\sigma \) and half above \( \mu + 1\sigma \). 3. **Calculate the Probability:** \[ P(X < 55) \approx \frac{32\%}{2} = 16\% \] Expressed as a decimal, this probability is **0.16**. ### Final Answer: The probability that \( X \) is less than 55 is **0.16**.

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To determine the probability that \( X \) is less than 55, we'll first find how many standard deviations away from the mean 55 is. The mean \( \mu \) is 73 and the standard deviation \( \sigma \) is 18. Calculating the z-score: \[ z = \frac{X - \mu}{\sigma} = \frac{55 - 73}{18} = \frac{-18}{18} = -1 \] According to the \( 0.68-0.95-0.997 \) rule, about 68% of the data falls within 1 standard deviation of the mean. Since the normal distribution is symmetric, this means that 34% falls between the mean and one standard deviation below it, and 34% also falls between the mean and one standard deviation above it. Thus, the area to the left of \( z = -1 \) (or \( X < 55 \)) is: \[ P(X < 55) = \text{Area to the left of mean} - \text{Area between mean and } z = -1 \] The total area to the left of the mean (73) is 0.5 (or 50%). Therefore, the probability that \( X \) is less than 55 is: \[ P(X < 55) = 0.5 - 0.34 = 0.16 \] Rounded to the nearest thousandth, the final answer is: \[ \boxed{0.160} \]

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