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Karl Pearson developed a measure that describes the skewness of

Karl Pearson developed a measure that describes the skewness of a distribution, called the coefficient of skewness. The formula is

Skewness = 3(mean — median) /standard deviation

The value of this measure generally lies between -3 and +3. The closer the value lies to -3, the more the distribution is skewed left. The closer the value lies to +3, the more the distribution is skewed right. A value close to 0 indicates a symmetric distribution. Find the coefficient of skewness of the following distributions and comment on the skewness.

(a) Mean = 50, median = 40, standard deviation = 10

(b) Mean = 100, median = 100, standard deviation = 15

(c) Mean = 400, median = 500, standard deviation = 120

(d) Compute the coefficient of skewness for the data in Problem 23.

(e) Compute the coefficient of skewness for the data in Problem 24.

Skewness = 3(mean — median) /standard deviation

The value of this measure generally lies between -3 and +3. The closer the value lies to -3, the more the distribution is skewed left. The closer the value lies to +3, the more the distribution is skewed right. A value close to 0 indicates a symmetric distribution. Find the coefficient of skewness of the following distributions and comment on the skewness.

(a) Mean = 50, median = 40, standard deviation = 10

(b) Mean = 100, median = 100, standard deviation = 15

(c) Mean = 400, median = 500, standard deviation = 120

(d) Compute the coefficient of skewness for the data in Problem 23.

(e) Compute the coefficient of skewness for the data in Problem 24.

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