Outlier Detection: What You Need to Know

https://hackernoon.com/outlier-detection-what-you-need-to-know

Analysts often encounter outliers in data during their work, such as during AB-test analysis, creating predictive models, or tracking trends. Decisions are usually based on the sample mean, which is very sensitive to outliers and can dramatically change the value. So, it is crucial to manage outliers to make the correct decision.

Let's consider several simple and fast approaches for working with unusual values.

Problem Formulation

Imagine that you need to conduct an experiment analysis using an average order value as a primary metric. Let's say that our metric usually has a normal distribution. Also, we know that the metric distribution in the test group is different from that in the control. In other words, the mean of the distribution in control is 10, and in the test is 12. The standard deviation in both groups is 3.

However, both samples have outliers that skew the sample means and the sample standard deviation.

https://hackernoon.com/outlier-detection-what-you-need-to-know