Understanding Inliers and Outliers in Statistics

Inlier refers to a data point that is considered to be part of the underlying population, and is therefore included in the analysis. In contrast, outliers are data points that do not fit the pattern of the other data points and are excluded from the analysis.

For example, if you were analyzing the heights of a group of people, an inlier would be someone who is of average height, while an outlier would be someone who is significantly taller or shorter than the rest of the group.

In statistics, inliers are often used to identify patterns and trends in data, and to exclude data points that do not fit those patterns. By excluding outliers and focusing on inliers, analysts can gain a better understanding of the underlying data and make more accurate predictions about future trends.

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