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It refers to asymmetry of any distribution. The symmetry of a distribution means that from a given deviation from a central value, there are equal number of observations on either side of the it.
If the distribution is asymmetrical or skewed, its frequency curve would have a prolonged tail either towards its left or right hand side.
Hence the Skewness of a distribution is defined as the departure form symmetry.
Symmetric or Normal Distribution
For a symmetrical distribution
Mean = Median = Mode
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Positively Skewed
For Positively Skewed distribution
Mode < Median < Mean
(i.e. more values are on the right hand side of the distribution than left)
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Negatively Skewed
For Negatively Skewed distribution
Mean < Median < Mode
(i.e. more values are on the left hand side of the distribution than Right)
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Measures of Skewness
Based on Measure of Mean, Median and Mode.
Based on Quartiles and Percentiles.
Based on Moments.
Based on Measure of Mean, Median and Mode
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Based on Quartiles and Percentiles
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Known as Bowly’s Coefficient of Skewness
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Value of coefficient of Skewness lies between - 1 and + 1
Based on Moments
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Measures of Kurtosis
A measure of coefficient of Kurtosis is given by Karl Pearson; That says if
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