To find the mean of the sampling distribution of the sample mean, we use the following formula:

$\mu_{\bar{x}} = \mu$

Where:

• $\mu_{\bar{x}}$ is the mean of the sampling distribution,
• $\mu$ is the population mean.

In this case, the population mean $\mu = 31$. Therefore, the mean of the sampling distribution is:

$\mu_{\bar{x}} = 31$

Answer: The mean of the sampling distribution is 31.

If you need further clarification or have other questions, feel free to ask!

Related Questions:

1. How does the standard deviation of the sampling distribution change with sample size?
2. What is the standard error of the mean for this case?
3. How is the sampling distribution related to the Central Limit Theorem?
4. How can I calculate the probability of obtaining a sample mean within a certain range?
5. What is the impact of increasing the sample size on the standard error?

Tip: The mean of the sampling distribution of the sample mean is always equal to the population mean, regardless of the sample size.