Answer:
Mean $1060
Standard error $34.69
Step-by-step explanation:
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, which is also called standard error, [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.
Population:
Mean $1,060 and standard deviation $190.
Sampling distriution of samples of size 30:
Mean $1060
Standard deviation [tex]s = \frac{190}{\sqrt{30}} = 34.69[/tex]
Answer:
Mean $1060
Mean $1060Standard error $34.69
