Handling Skew in Data

Data skew refers to the asymmetry or lack of balance in the distribution of data within a dataset. When data is skewed, it tends to cluster more heavily toward one end of the scale, creating what is often referred to as a long tail on one side of the distribution curve, that is, the values are not evenly distributed across the range.

Imagine a histogram or a bell curve representing the distribution of data points. In a skewed distribution, instead of a symmetrical bell shape, you can see that the curve is stretched out to one side with relatively fewer data points on the other side. This long tail indicates that outliers or extreme values are pulling the distribution away from the center.

In a positively skewed distribution, the tail extends toward the higher end of the scale, indicating that some very high values are relatively rare compared to the majority of the data. Conversely, in a negatively skewed distribution, the tail extends toward the lower end...