The Central Limit Theorem is a powerful statistical tool because it: a. Allows us to use population data to reach a conclusion about samples b. Allows us to use sample type data to reach conclusions about the population c. Allows us to more accurately draw a frequency distribution d. Allows us to make use of the t-statistic.
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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.
Frank D.
The Central Limit Theorem is important in statistics because A) for any population, it says the sampling distribution of the sample mean is approximately normal, regardless of the sample size. B) for any sized sample, it says the sampling distribution of the sample mean is approximately normal. C) for a large n, it says the sampling distribution of the sample mean is approximately normal, regardless of the shape of the population. D) for a large n, it says the population is approximately normal.
Benjamin D.
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