Chapter 3 Skewness
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Project on Skewness
Skewness in mathematics, particularly in statistics, refers
to the measure of asymmetry of the probability distribution of a real-valued
random variable about its mean. In simpler terms, it indicates whether the data
is symmetrically distributed or not.
If the distribution of data points is symmetric, meaning it
looks the same on both sides of the mean, then the skewness is zero. However,
if the distribution is skewed to the left or right, the skewness will be
negative or positive, respectively.
A positive skewness indicates that the tail on the right
side of the distribution is longer or fatter than the left side, and the mean
is greater than the median. Conversely, a negative skewness means the tail on
the left side of the distribution is longer or fatter than the right side, and
the mean is less than the median.
Skewness is an important measure in understanding the shape of data distributions and is often used in various statistical analyses and applications.