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- What Are outliers?
- Example: Using The Interquartile Range to Find Outliers
- Dealing with Outliers
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Outliers are values at the extreme ends of a dataset. Some outliers represent true values from natural variation in the population. Other outliers may result from incorrect data entry, equipment malfunctions, or other measurement errors. An outlier isn’t always a form of dirty or incorrect data, so you have to be careful with them in data cleansing...
We’ll walk you through the popular IQR method for identifying outliers using a step-by-step example. Your dataset has 11 values. You have a couple of extreme values in your dataset, so you’ll use the IQR method to check whether they are outliers.
Once you’ve identified outliers, you’ll decide what to do with them. Your main options are retaining or removing them from your dataset. This is similar to the choice you’re faced with when dealing with missing data. For each outlier, think about whether it’s a true value or an error before deciding. 1. Does the outlier line up with other measureme...
If you want to know more about statistics, methodology, or research bias, make sure to check out some of our other articles with explanations and examples.
Learn what outliers are, how to identify them, and how to deal with them in your data analysis. This article explains four methods to detect outliers with examples and explanations.
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Aug 24, 2021 · Learn the definition and methods of detecting outliers in a dataset using the interquartile range. Follow the steps and examples for odd and even datasets to calculate Q1, Q3, IQR and outliers.
Box plot of data from the Michelson–Morley experiment displaying four outliers in the middle column, as well as one outlier in the first column. In statistics , an outlier is a data point that differs significantly from other observations.
Sep 28, 2023 · Learn what outliers are, how they affect data analysis, and how to identify and handle them. Find out the causes, types, and methods of outlier detection with examples and visualizations.
Outliers are data points that are far from other data points and can affect statistical analyses. Learn five methods to identify outliers, such as sorting, graphing, and using Z-scores, and see examples and comparisons.
Oct 4, 2022 · Learn what outliers are, how to identify them, and how to deal with them in your data analysis. This web page explains four methods to detect outliers: sorting, data visualisation, statistical tests, and interquartile range.
