Step 1 :The mean of the sample means, denoted as \( \mu_{\bar{x}} \), is equal to the population mean, \( \mu \). So, \( \mu_{\bar{x}} = \mu = 32 \).
Step 2 :The standard deviation of the sample means, denoted as \( \sigma_{\bar{x}} \), is equal to the population standard deviation, \( \sigma \), divided by the square root of the sample size, \( n \). So, \( \sigma_{\bar{x}} = \frac{\sigma}{\sqrt{n}} \).
Step 3 :Let's calculate \( \sigma_{\bar{x}} \) using the given values of \( \sigma = 2 \) and \( n = 25 \).
Step 4 :After executing this calculation, we get the value of \( \sigma_{\bar{x}} = 0.4 \).
Step 5 :Final Answer: \[ \begin{array}{l} \mu_{\bar{x}}=\boxed{32} \ \sigma_{\bar{x}}=\boxed{0.4} \end{array} \]