Final answer:
The distribution of the means, also known as the sampling distribution of the sample mean, will have a mean of 50, identical to the parent population mean, due to the central limit theorem.
Step-by-step explanation:
If the parent population has a mean of 50 and a standard deviation of 10, then the distribution of the means (also known as the sampling distribution of the sample mean) will also have a mean that is the same as the parent population mean, which is 50. This is a result of the central limit theorem, which states that the sampling distribution of the sample mean will be normally distributed around the population mean regardless of the distribution of the parent population, provided the sample size is sufficiently large.
In terms of the sampling distribution, if you draw 100 samples of size 40 from this population, you would expect to see that the distribution of the sample means clusters around the population mean of 50. Each individual sample may have a mean that varies due to sampling variability, but when aggregated into a distribution, they will form a normal distribution centered at the population mean.