I If a Population Is Not Normally Distributed, the Sampling

i. If a population is not normally distributed, the sampling distribution of the sample means tends to approximate a normal distribution. ii. The Central Limit Theorem states that if the sample size n is sufficiently large, the sampling distribution of the means will be approximately normal no matter whether the population is normally distributed, skewed, or uniform.
iii. Based on the sampling distribution of the means and the central limit theorem, the sample mean can be used as a good estimator of the population mean, assuming that the size of the sample is sufficiently large.

A) (i) , (ii) , and (iii) are all correct statements.
B) (i) is a correct statement, but not (ii) or (iii) .
C) (ii) is a correct statement, but not (i) or (iii) .
D) (ii) and (iii) are correct statements but not (i) .
E) (i) , (ii) , and (iii) are all false statements.