INFORMATION OF SKEWNESS

SKEWNESS

   The word skewness means ‘‘lacking symmetry’’.  In a normal distribution the mean, median and mode coincide. Then the right and left half in the curve will be in symmetry. But when the mean and median fall at the different points in the distribution, the symmetry is lost.  Then the curve is said to be skewed.  Depending on the nature of the shifting of the centre of gravity to the right or left,  Skewness can be positive or negative. Skewness is asymmetry in a statistical distribution, in which the curve appears destroyed or skewed either to the right.  Skewness can be quantified to define the extent to which a distribution differs from a normal distribution.

  Figure1: skewnesscurve   

TYPES OF SKEWNESS

Thus,  a statistical distribution may be three types viz.

·        Symmetric.

·        Positively skewed.

·        Negatively skewed

                          Symmetric.

                          A symmetric distribution is never a skewed distribution.  The normal distribution is symmetric.  It is also a unimodel distribution.

                          Positively skewed.

                          A distribution is said to be positively skewed or skewed to the right when the scores are massed at the left end and spread out gradually to the right end.

                          Negatively skewed.

                          A distribution is said to be skewed negatively when the scores are massed at the right end,  and spread out gradually to the left end.

Table1: Brief note of skewness

Types of skewness	scores	Ending
Symmetric	Normal	Normal
Positive	Massed at the left end	Right end
Negatively	Massed at the right end	Left end

            In conclusion,  the skewness coefficient of a set of the distribution curve,  whether it’s positive or negative.