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: . The sampling distribution of the mean will be approximately normal when n 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 shape of the sampling distribution is closer to the population shape as the sample size increases. - The sampling distribution is always approximately normal even if the population is not normal. . If a population is perfectly normal, then for the distribution of sample means of any size, pi = [A and 05; = a. T - If the population is normally distributed, then sample size does not matter for the central limit theorem to apply. , - From the same population, the mean of the sampling distribution (pi) with n = 10 will be smaller than the mean with n = 16. . The smaller the sample size, the larger the standard error. - From the same population, the standard error of the sampling distribution with n = 18 will be larger than the standard error with n = 41. . The smaller the sample size, the smaller the difference between the mean of the sampling distribution and the population mean. a - If p5 = p and 05 = , then the distribution of sample means is normal. n