The level of cholesterol in the blood for all men aged 20 to 34 follows a Normal distribution when mean \( \mu_{M}=188 \) milligrams © BFW Publishers per deciliter ( \( \mathrm{mg} / \mathrm{dl} \) ) and standard deviation \( \sigma_{M}=41 \mathrm{mg} / \mathrm{dl} \). For 14 -year-old boys, blood cholesterol levels follow a Normal distribution with mean \( \mu_{B}=170 \mathrm{mg} / \mathrm{dl} \) and standard deviation \( \sigma_{B}=30 \mathrm{mg} / \mathrm{dl} \). Suppose we select independent SRSs of 25 men aged 20 to 34 and 36 boys aged 14 and calculate the sample mean cholesterol levels \( \bar{x}_{M} \) and \( \bar{x}_{B} \). What is the probability of getting a difference in sample means \( \bar{x}_{M}-\bar{x}_{B} \) that's less than \( 0 \mathrm{mg} / \mathrm{dl} \) ? Round to 4 decimal places.
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To find the probability of \( \bar{x}_{M} - \bar{x}_{B} < 0 \), we first need to calculate the distributions of the sample means. For the men, the mean is \( \mu_{M} = 188 \) mg/dl and the standard error (SE) of the sample mean is \( \sigma_{M} / \sqrt{n_{M}} = 41 / \sqrt{25} = 8.2 \) mg/dl. For the boys, the mean is \( \mu_{B} = 170 \) mg/dl and the SE is \( \sigma_{B} / \sqrt{n_{B}} = 30 / \sqrt{36} = 5 \) mg/dl. Next, we find the mean and standard deviation of the difference in sample means: \[ \mu_{\bar{x}_{M} - \bar{x}_{B}} = \mu_{M} - \mu_{B} = 188 - 170 = 18 \text{ mg/dl} \] \[ \sigma_{\bar{x}_{M} - \bar{x}_{B}} = \sqrt{(8.2)^2 + (5)^2} = \sqrt{67.24 + 25} = \sqrt{92.24} \approx 9.61 \text{ mg/dl} \] Now, we standardize the difference to find the Z-score for 0: \[ Z = \frac{0 - 18}{9.61} \approx -1.87 \] Using standard normal distribution tables or calculators, we find the probability corresponding to \( Z = -1.87 \). This gives us: \[ P(Z < -1.87) \approx 0.0301 \] Thus, the probability of getting a difference in sample means \( \bar{x}_{M} - \bar{x}_{B} < 0 \) is approximately **0.0301** when rounded to four decimal places.