A population of values has a normal distribution with \( \mu=145.2 \) and \( \sigma=91.6 \). You intend
to draw a random sample of size \( n=204 \).
Find the probability that a single randomifsselected value is between 133 and 161.9 .
\( P(133
Ask by Morgan Cervantes. in the United States
Mar 16,2025
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To solve the problems, we first need to calculate the \( z \)-scores for the individual value and the sample mean.
### Step 1: Find \( P(133 < X < 161.9) \)
1. Calculate the \( z \)-scores for 133 and 161.9 using the formula:
\[
z = \frac{X - \mu}{\sigma}
\]
For \( X = 133 \):
\[
z_{133} = \frac{133 - 145.2}{91.6} \approx -0.132
\]
For \( X = 161.9 \):
\[
z_{161.9} = \frac{161.9 - 145.2}{91.6} \approx 0.182
\]
2. Now, we refer to the standard normal distribution table or use a calculator to find the probabilities:
\[
P(Z < -0.132) \approx 0.4483 \quad \text{and} \quad P(Z < 0.182) \approx 0.5714
\]
3. The probability \( P(133 < X < 161.9) \):
\[
P(133 < X < 161.9) = P(Z < 0.182) - P(Z < -0.132) \approx 0.5714 - 0.4483 = 0.1231
\]
### Step 2: Find \( P(133 < M < 161.9) \)
For the sample mean, we need to adjust the standard deviation using the sample size \( n \):
1. Calculate the standard error \( \sigma_M \):
\[
\sigma_M = \frac{\sigma}{\sqrt{n}} = \frac{91.6}{\sqrt{204}} \approx 6.372
\]
2. Calculate the \( z \)-scores for 133 and 161.9 using \( \sigma_M \):
For \( M = 133 \):
\[
z_{133} = \frac{133 - 145.2}{6.372} \approx -1.912
\]
For \( M = 161.9 \):
\[
z_{161.9} = \frac{161.9 - 145.2}{6.372} \approx 2.663
\]
3. Find the probabilities:
\[
P(Z < -1.912) \approx 0.0281 \quad \text{and} \quad P(Z < 2.663) \approx 0.9963
\]
4. The probability \( P(133 < M < 161.9) \):
\[
P(133 < M < 161.9) = P(Z < 2.663) - P(Z < -1.912) \approx 0.9963 - 0.0281 = 0.9682
\]
### Final Answers:
- \( P(133 < X < 161.9) \approx 0.1231 \)
- \( P(133 < M < 161.9) \approx 0.9682 \)
So, the answers rounded to four decimal places are:
\( P(133