The time that a randomly selected individual waits for an elevator in an office building has a uniform distribution over the interval from 0 to 1 minute. For this distribution μ = 0.5 and σ = 0.289. (a) Let x be the sample mean waiting time for a random sample of 12 individuals. What are the mean and standard deviation of the sampling distribution of x? (Round your answers to three decimal places.)

The Central Limit Theorem estabilishes 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 Central Limit Theorem can also be applied, as long as n is at least 30.

For the population, we have that:

Mean = 0.5

Standard deviaiton = 0.289

Sample of 12

By the Central Limit Theorem

Mean = 0.5

Standard deviation [tex]s = \frac{0.289}{\sqrt{12}} = 0.083[/tex]

The mean of the sampling distribution of x is 0.5 and the standard deviation is 0.083.