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Friday, November 9, 2018
Saturday, November 3, 2018
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.
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