Final answer:
The standard error of the sample mean can be found by dividing the standard deviation of the population by the square root of the sample size. The distribution of the sample mean would be approximately normal, with a mean equal to the population mean and a standard deviation equal to the population standard deviation divided by the square root of the sample size.
Step-by-step explanation:
The standard error of the sample mean can be found by dividing the standard deviation of the population by the square root of the sample size. So in this case, if we have a standard normal random variable with a mean of 0 and standard deviation of 1, the standard error of the sample mean would be 1 divided by the square root of the sample size. The distribution of the sample mean would be approximately normal, with a mean equal to the population mean and a standard deviation equal to the population standard deviation divided by the square root of the sample size. In this case, the mean would still be 0 and the standard deviation would be 1 divided by the square root of the sample size.