Suppose that many large samples were taken from population A, which is normally distributed, and population c, which is not normally distributed. The means of samples of which of the following populations would approximate a normal distribution?
I think the answer is A. Population A I just want to make sure I wasn't reading anything wrong and that I understood the question correctly.
Hmmm ever heard of central limit theorem?
@KJ4UTS ?
The question is actually referring to the sampling distributions of Pop A and Pop B Its basically asking if the sampling distributions are normally distributed? The sampling distribution is basically the distribution of all the means of the various samples. So for instance we took 10 different samples from population A and the sampling distribution basically tracks the means of all these samples. The central limit theorem states that if the samples are large enough meaning they are over 30 thennn it Makes no difference if the population is normally distributed BUT the sampling distribution will always be normally distributed
@samjordon so is it population A?
No lol
Are you in hs? Have you learned the central limit theorem?
yeah im in hs but I we just started this unit on these concepts and im still a little confused.
hmmm the central limit theorem states That even if the population is NOT Normally distributed, the distribution of mean of the many samples you have taken will be normal
hmmm you should watch this video https://www.khanacademy.org/math/probability/statistics-inferential/sampling_distribution/v/central-limit-theorem
oh so if the population is NOT Normally distributed that would include population c also?
Yes lol This is only for very large samples
So D. Both population A and population C
And its not referring to the sample ... its referring to the sample distribution So you took 40 samples and each of these samples had a mean So then the the distributions of all these means would be normal
yes
Thank you for your time and help :)
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