Skewness

Skewness:

In Statistics we have numerous distribution and every distribution has his own graph and interpretation. Likewise, in skewness we use central tendency (Mean, Mode, Median) and construe it accordingly. Therefore, skewness is a tool that assist us to interpret  central distribution or central location through  following three ways:

Positively Skewed:

In positively skewed, mean is always greater as compare to mode, median and mode is always less then median. In mathematically we can write it as:

Mean > Median> Mode = Mode< Median< Mean

Here graph shows that the data is Positively skewed and has right tail.

Negatively Skewed:

In negatively skewed, mode is always greater as compare to mean and median, mean is always less then median. In mathematically we can write it as:

Mean < Median < Mode = Mode >Median > Mean

Here graph shows that the data is Natively skewed  and has left tail.

Symmetric  or Skewed:

In symmetric or skewed, mean, mode and median are equal to each other and it has no tail.

Mean = Mode=Median

Here graph shows that the data is symmetric.