Outlier Examples
Example 1: Dataset: 10, 12, 14, 16, 18, 500
Solution:
Outlier Calculation: Using the IQR method,
Q1 = 12, Q3 = 18
IQR = Q3 – Q1 = 6
Lower Bound = Q1 – 1.5 * IQR = 3
Upper Bound = Q3 + 1.5 * IQR = 27
The value 500 is an outlier.
Example 2: Dataset: 20, 22, 24, 26, 28, 30
Solution:
Outlier Calculation: Using Z-score,
Mean = 25, Standard Deviation = 4
Z-score for 30 = (30 – 25) / 4 = 1.25
The value 30 is not an outlier.
Outlier
Outliers stand for data points that are indicative of a much higher variability than other observations in a given dataset. This can result in skewing statistical studies and wrong conclusions after all the variables are not adequately identified and handled. Identifications of outliers are very relevant for the financial sector, healthcare industry and decision-making processes that depend on data analysis.
In this article, we will learn in detail about outlier, its definition, examples, types, how to find outlier, their uses and how they are different of inliers.