Suppose Y is a random variable with mu Subscript Upper YμY = 0, and sigma Subscript Upper Y Superscript 2σ2Y = 1, skewness = 0, and kurtosis = 100. Explain why n random variables drawn from this distribution might have some large outliers.

A. There might be some outliers because the kurtosis of the distribution equals 100.

B. There might be some large outliers because both, the population variance sigma Subscript Upper Y Superscript 2σ2Y and standard deviation sigma Subscript Upper YσY , are equal to 1.

C. There might be some outliers because the skewness of the distribution equals 0.

D. There might be some large outliers because the population mu Subscript Upper YμY equals 0.

Question

Business

Emery Lynch

16 January, 18:16

Suppose Y is a random variable with mu Subscript Upper YμY = 0, and sigma Subscript Upper Y Superscript 2σ2Y = 1, skewness = 0, and kurtosis = 100. Explain why n random variables drawn from this distribution might have some large outliers.

A. There might be some outliers because the kurtosis of the distribution equals 100.

B. There might be some large outliers because both, the population variance sigma Subscript Upper Y Superscript 2σ2Y and standard deviation sigma Subscript Upper YσY , are equal to 1.

C. There might be some outliers because the skewness of the distribution equals 0.

D. There might be some large outliers because the population mu Subscript Upper YμY equals 0.

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Answers (1)

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Joseph Blackburn · Answer 1

Suppose Y is a random variable with mu Subscript Upper YμY = 0, and sigma Subscript Upper Y Superscript 2σ2Y = 1, skewness = 0, and kurtosis = 100.

n random variables drawn from this distribution might have some large outliers due to the reason that there might be some outliers because the kurtosis of the distribution equals 100 ...

Option A.

Explanation:

From the question, the rate of the description of the data given will not give rise to outliers in the random sample drawn from the population.

Therefore, there might be some outliers because the kurtosis of the distribution equals 100 - Option A.