How is the lower limit for outliers determined?

The lower limit for identifying outliers is determined using the formula Q1 - 1.5(IQR), where Q1 represents the first quartile and IQR stands for the interquartile range (which is the difference between the third quartile, Q3, and the first quartile, Q1).

This method is based on the idea that any data point that falls significantly below the lower quartile (Q1) can be considered an outlier. The factor of 1.5 is a commonly accepted threshold that indicates a distance far enough from the central tendency (in this case, the middle 50% of the data) to warrant classification as an outlier.

Thus, if a data point is smaller than this calculated lower limit, it would be considered an outlier and may need further investigation to understand if it is a result of a data entry error, a unique occurrence, or part of the normal variation in the data. This approach effectively highlights extreme values that could skew results and insights derived from the dataset.