0:22 Overview of Sampling Distribution 3:12 Central Limit Theorem 4:40 z-Value for Sampling Distribution (Standardizing) 5:40 Practice Problem 7.2.23 10:00 Excel Demo of 7.2.23
note to self: theorem 1: studying the mean of a sample is the same as the mean of the entire population central Limit theorem: for any sample size, it eventually reaches a normal distribution if the sample population is large enough
@9:40 ... cumulative (true) means Excel is adding all the probabilities to the LEFT. That is why you need to subtract it from 1 to get all the probabilities to the RIGHT. You should put a correction in this video.
Thnx
note to self: theorem 1: studying the mean of a sample is the same as the mean of the entire population central Limit theorem: for any sample size, it eventually reaches a normal distribution if the sample population is large enough
@9:40 ... cumulative (true) means Excel is adding all the probabilities to the LEFT. That is why you need to subtract it from 1 to get all the probabilities to the RIGHT. You should put a correction in this video.
Thank you keep it up
in z equation, sigma/square root of n is the srandard error
Thank you so much.