How do the t and z distribution differ? The t distribution has broader tails (it

Question

How do the t and z distribution differ? The t distribution has broader tails (it is flatter around zero). There is no difference between the r and z distribution The z distribution has asymptotic tails, while the t distribution does not. The z distribution has broader tails (it is flatter around zero) What are required by the central limit theorem before a confidence interval of the population mean may be created? The underlying population need not be normally distrusted if the sample size is 30 or more The underlying population must be normally distributed. The underlying population need not be normally distributed if the population standard deviation is know. The underlying mean be normally distributed if the sample size is 30 or more.

Explanation / Answer

Question 9

answer:

When used for sample means, the z-distribution assumes that you know the POPULATION standard deviation (which is never the case).

The t-distribution is based on using the sample standard deviation as an estimate of the population standard deviation. Approximating the population standard deviation with a sample standard deviation means the sampling distribution is going to have more spread and is going to be affected by the sample size.

Hence for any test statistic value (t=+/-2 vs z=+/-2) there will be a higher proportion outside those endpoints for the t-distribution.

Correct answer would be A. t distribution has broader tail

Hope this helps you:-)

Thanks and Post remaining question saperately.

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