Which of the following about Central Limit Theorem is NOT correct? . A. will ena

Question

Which of the following about Central Limit Theorem is NOT correct? . A. will enable one to develop the sampling distribution of the mean in some situations following normal distribution even if the population distribution is not normally distributed. B. Regardless the underlying population distribution, if the sample size taken is large enough, the sampling distribution of the mean will approximately follows normal distribution. C. Allow one to determine standard error of the mean. D. If the underlying population follows normal distribution, the sampling distribution of the mean will always follow normal distribution

Explanation / Answer

Central Limit Theorem

The distribution of an average tends to be Normal, even when the distribution from which the average is computed is decidedly non-Normal.

option 4 (always) is not correct, because one can approximately draw normal or data can be made into normal, but we wont get always normal distribution.

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For samples we use t-test if N<30, else Z-test N>30

For overall population we use Z-test

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T-value for 98% confidence limit and DoF=15 is

98% confidence limit means 2% error limit or significance limit

For two-tailed test 1% on either side of normal distribution

0.01 significance limit and DoF=15 , check in table

answer is 2.6025

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