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. Compute the coefficient of skewness

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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.

Compute the coefficient of skewness for the data in Problem 25

Problem 25 data: The following data (see photo) represent the weights (in grams) of random sample of 50 M&M plain candies.

0.87
0.88
0.82
0.90
0.90
0.84
0.84
0.91
0.94
0.86
0,86
0.86
0,88
0.87
0.89
0.91
0.86
0.87
0.93
0.88
0.83
0.95
0.87
0.93
0.91
0.85
0.91
0.91
0.86
0.89
0.87
0.84
0.88
0.88
0.89
0.79
0.82
0.83
0.90
0.88
0.84
0.93
0.81
0.90
0.88
0.92
0.85
0.84
0.84
0.86
Source: Michael Sullivan.
Transcribed Image Text:0.87 0.88 0.82 0.90 0.90 0.84 0.84 0.91 0.94 0.86 0,86 0.86 0,88 0.87 0.89 0.91 0.86 0.87 0.93 0.88 0.83 0.95 0.87 0.93 0.91 0.85 0.91 0.91 0.86 0.89 0.87 0.84 0.88 0.88 0.89 0.79 0.82 0.83 0.90 0.88 0.84 0.93 0.81 0.90 0.88 0.92 0.85 0.84 0.84 0.86 Source: Michael Sullivan.
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Coefficient of skewness = 3 (mean-median)/standard deviation

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