Which of the following statements about the sampling distribution of the mean (distribution of sample means) and the central limit theorem (CLT) are true?

Select four (4) true statements from the list below: ' - From the same population, the standard error of the sampling distribution with n = 18 will be the same as the standard error with n = 45. - The sampling distribution of the mean will be approximately normal when p is large. ' - The sampling distribution is still assumed to be approximately normal if the underlying population is nonnormal as long as the population is large. - The sampling distribution will be approximately normal even if the population is not normal as long as the sample size is large. - If the population is uniformly distributed, then sample size does not matter for the central limit theorem to apply. ' - From the same population, the mean of the sampling distribution (#5) with n = 6 will be larger than the mean with n = 13. - The smaller the sample size, the smaller the difference between the mean of the sampling distribution and the population mean. ' - If a population is perfectly normal, then for the distribution of sample means of any size, p5 = p, and 05 = a. - The shape of the sampling distribution is closer to a normal curve as the sample size increases. - The larger the sample size, the smaller the standard error. a - p5. = ,u, and 05, = f for the sampling distribution of the mean whether or n not the population is normal