High School

A population has parameters \( p = 239.5 \) and \( \sigma = 97.6 \). You intend to draw a random sample of size \( n = 145 \).

1. What is the mean of the distribution of sample means?
2. What is the standard deviation of the distribution of sample means? (Report answer accurate to 2 decimal places.)

\(\sigma_{\bar{x}}\) =

Answer :

Final answer:

The mean of the distribution of sample means is equal to the population mean, which is 239.5 in this case. The standard deviation of this distribution, or the standard error, is the population standard deviation divided by the square root of the sample size, which equals 8.08.

Explanation:

The question involves the concept of the distribution of sample means, also known as the sampling distribution. This derives from the Central Limit Theorem in statistics.

The mean of the distribution of sample means is equal to the mean of the population, which is the parameter p. In this case, the mean µ = p = 239.5.

The standard deviation of the distribution of sample means, also known as the standard error, is the population standard deviation o divided by the square root of the sample size n. So, The standard deviation of the distribution of sample means = o / √n = 97.6 / √145 = 8.08 (to 2 decimal places).

Learn more about Sampling Distribution here:

https://brainly.com/question/39609355

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