Basics of ML & AL Week 2 Challenge

Skewness:

Skewness refers to a distribution or asymmetry that deviates from the symmetrical bell curve, or normal distribution, in a set of data. If the curve iis shifted to the left or to the right, it is aid to be skewed. Skewness can be quantified as a representation of the extent to which a given distribution varies from a normal distribution. A normal distribution has a skew of zero, while lognormal distribution for example would exhitbit some degree of right skew.

1.Skewness in statistics is the degree of aymmetry observed in a probability distribution.

2.Distribution can exibit right skewness or left skewness to varying degree. A normal distribution exhibits zero skewness.

The mean of positively skewed data will greater than the median. In a distribution that is negatively the exact opposite is the case. The mean of negatively skewed data will be less than the median. If the data graphs symmetrically, the distribution has zero skewness, regardless of how long or fat the tails are.