According to the central limit theorem, group of answer choices a) the population mean and the mean of all sample means are equal. b) increasing sample size decreases the dispersion of the sampling distribution. c) the sampling distribution of the sample means is approximately normally distributed. d) the sampling distribution of the sample means will be skewed.

this is a good question! i’ll do some research and what i find, i’ll contact you asap when i have something! ✊

irst, find the z score of a score of 80. this is given by the formula z = (x-u)/o, where x is the score, u is the mean, and o is the standard deviation. this gives

z = (80-78)/12 = 1/6 = .1667

now, find what percentile a z score of 1/6 correlates to in the normal distribution.

a z score of 1/6 = .1667 is equivalent to the 56.36th percentile of the distribution. so the probability a score is over this is 1-.5636 = .4364

the mean of a sample mean is equal to the original mean. however, the standard deviation of a sample mean is equal to the original standard deviation divided by the square root of n (sample size). so the new standard deviation is 12/sqrt(16) = 3.

the new z score is 80-78/3 = 2/3 = .667. this is equivalent to the 74.86th percentile. so the probability that the mean will be greater than this score is 1-.7486 = .2514.