The central limit theorem is important for all of the following reasons except: It ensures that the sampling distribution of the sample mean approaches normal as the sample size increases. It allows us to use information from samples to draw conclusions about population parameters without knowing the shape of the population distribution. It ensures that the samples we select are random and representative. It allows us to use the normal distribution in statistical tests on sample means. None of the above.

Question

Travis Gilmore

Mathematics

4 April, 16:27

The central limit theorem is important for all of the following reasons except: It ensures that the sampling distribution of the sample mean approaches normal as the sample size increases. It allows us to use information from samples to draw conclusions about population parameters without knowing the shape of the population distribution. It ensures that the samples we select are random and representative. It allows us to use the normal distribution in statistical tests on sample means. None of the above.

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Answers (1)

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Markus Wu · Answer 1

E. None of the above.

Step-by-step explanation:

The central limit theorem states that; the sampling distribution of a population mean tends towards a normal distribution with respect to an increasing sample size. It implies that as the sample size increases, the shape of a sampling distribution would approach normality as required.

Therefore, most options in the given question are importance of the theorem. Thus, none of the above is the correct choice because other choices are directly or indirectly an importance of central limit theorem.