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What does the central limit theorem state?

a: if the sample size increases sampling distribution must approach normal distribution Explanation

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b: if the sample size decreases then the sample distribution must approach normal distribution Explanation

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c: if the sample size increases then the sampling distribution much approach an exponential distribution Explanation

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d: if the sample size decreases then the sampling distribution much approach an exponential distribution Explanation

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The Central Limit Theorem says that the sampling distribution of the sample mean is approximately normal if?

a: all possible samples are selected Explanation

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b: the sample size is large Explanation

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c: the standard error of the sampling distribution is small. Explanation

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d: the sample size is small Explanation

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The Central Limit Theorem says that the mean of the sampling distribution of the sample means is?

a: equal to the population mean divided by the square root of the sample size Explanation

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b: close to the population mean if the sample size is large Explanation

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c: exactly equal to the population mean Explanation

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d: equal to the population mean divided by the sample size Explanation

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The Central Limit Theorem says that the standard deviation of the sampling distribution of the sample means is ?

a: equal to the population standard deviation divided by the square root of the sample size Explanation

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b: close to the population standard deviation if the sample size is large Explanation

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c: exactly equal to the standard deviation Explanation

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d: equal to the population standard deviation divided by the sample size Explanation

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Samples of size 25 are selected from a population with mean 40 and standard deviation 7.5. The mean of the sampling distribution of sample means is?

a: 7.5 Explanation

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b: 8 Explanation

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c: 40 Explanation

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d: 60 Explanation

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Central limit theorem