How is an outlier generally determined?

An outlier is typically determined by evaluating the interquartile range (IQR) of a data set, which measures the spread of the middle 50% of the data. The formula QL - 1.5 x IQR is specifically used to find the lower boundary below which data points are considered potential outliers. In this context, QL refers to the first quartile, which is the median of the lower half of the data. If a data point falls below this calculated lower boundary, it is identified as an outlier.

Using the IQR to identify outliers is effective because it focuses on the variability of the bulk of the data rather than being influenced by extreme values. The corresponding upper boundary for outliers is established using the formula QH + 1.5 x IQR, where QH is the third quartile. This comprehensive approach ensures that data points that are either significantly lower or higher than the general concentration of the data can be properly identified as outliers.