# Winsorized Mean Calculator Calculate a winsorized mean by capping extreme low and high values before averaging > Canonical page: https://elysiatools.com/en/tools/winsorized-mean-calculator - **Category:** Math & Numbers - **Keywords:** winsorized mean, winsorized average, statistics, outliers, robust average ## Overview Calculate a winsorized mean for a numeric dataset. A winsorized mean sorts the data, caps the lowest and highest tail values to the nearest retained boundary values, then averages the adjusted dataset. Use it when outliers should be limited rather than removed, such as finance, operations metrics, survey analysis, and robust dashboards. ## Inputs - **Dataset** (textarea): e.g. 10, 12, 14, 16, 18, 100 - **Winsor Percent Per Tail** (number) - **Decimal Places** (number) - **Include Winsorized Dataset** (checkbox) ## When to use - When you want to reduce the impact of extreme outliers without completely removing data points from your sample size. - When analyzing financial returns or operational metrics where occasional spikes or drops distort the standard average. - When processing survey results or performance scores that contain anomalous but valid extreme responses. ## How it works - Enter your numeric dataset as a comma-separated list in the input field. - Specify the percentage of data to winsorize from each tail (e.g., 10% replaces the bottom 10% and top 10% of values). - Choose the desired number of decimal places for the final calculation. - The tool sorts the data, caps the extreme values at the specified percentiles, and calculates the adjusted mean. ## Use cases - Calculating average employee salaries while mitigating the skew caused by a few executive compensation packages. - Evaluating average server response times where occasional network timeouts create artificially high spikes. - Analyzing customer satisfaction survey scores to prevent a small number of extreme ratings from distorting the overall consensus. ## Frequently asked questions ### What is a winsorized mean? A winsorized mean is a robust statistical measure that calculates the average of a dataset after replacing its extreme high and low values with the most extreme remaining values. ### How is winsorizing different from trimming? Trimming completely removes the extreme values from the dataset before averaging, whereas winsorizing replaces those extreme values with the nearest retained boundary values, keeping the sample size exactly the same. ### What does the 'Winsor Percent Per Tail' mean? It defines the percentage of data points at both the lowest and highest ends of your sorted dataset that will be capped. For example, a 10% winsor percent affects the bottom 10% and top 10% of your data. ### Can I see the adjusted dataset after winsorizing? Yes, by checking the 'Include Winsorized Dataset' option, the tool will output the modified dataset alongside the final calculated mean. ### What is the maximum percentage I can winsorize? You can winsorize up to 45% per tail. 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