1. Physicians There are about 900,000 active physicians in the United States, and they have annual incomes with a distribution that is skewed instead of being normal. Many different sam- ples of 40 physicians are randomly selected, and the mean annual income is computed for each sample.
a. What is the approximate shape of the distribution of the sample means (uniform, normal, skewed, other)?
b. What value do the sample means target? That is, what is the mean of all such sample means?

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the sampling distribution is also approximately normal, as long as n is at least 30.

Item a:

The variable is skewed, however, the sample size is greater than 30, hence the approximate shape of the distribution is normal.

Item b:

According to the mean of the sampling distributions, given by the Central Limit Theorem, it targets the population mean.

More can be learned about the Central Limit Theorem at https://brainly.com/question/24663213