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Trimmed Mean Calculator

Calculate a trimmed mean - a robust average that removes a percentage of extreme values from each end before averaging.

Result

Trimmed Mean
9.7778
Regular Mean (for comparison)
9.7778
Values Removed (each end)
0

About the Trimmed Mean Calculator

The Trimmed Mean Calculator computes a robust average by removing a set percentage of the highest and lowest values from a dataset before averaging what remains. It is useful whenever a few extreme values would otherwise distort a plain mean, such as judged scoring systems or noisy measurement data.

How It Works

Enter a list of numbers and a trim percentage to remove from each end. The calculator sorts the values, calculates how many values that percentage represents at each end (rounded down), strips that many values from the bottom and top of the sorted list, and averages what is left. It also reports the regular untrimmed mean and the count of values removed from each end for comparison.

trimCount = floor(n x trim percentage); trimmed mean = average of the sorted values after removing trimCount values from each end.

Formula & Methodology

To calculate by hand, sort your data from smallest to largest, then multiply the total count by your chosen trim percentage and round down to find how many values to drop from each end. Remove that many values from both the bottom and top of the sorted list, then take the ordinary average of what remains. At 0 percent trim this equals the regular mean, and as the percentage rises toward 50 percent it approaches the median.

Examples

Removing a Scoring Outlier

With the values 2, 4, 5, 5, 6, 6, 7, 8, 45 (nine values) and a 10 percent trim, trimCount = floor(9 x 0.10) = 0, so no values are removed and the trimmed mean equals the regular mean of about 9.78.

Judging Panel Scores

With ten scores and a 20 percent trim, trimCount = floor(10 x 0.20) = 2, so the two lowest and two highest scores are dropped, leaving six middle scores to average.

Advantages

  • Reduces the influence of extreme outliers without discarding as much information as the median does.
  • Reports the regular mean alongside the trimmed mean, making it easy to see how much outliers were pulling the average.
  • Shows the number of values actually removed from each end, flagging cases where a chosen trim percentage rounds down to zero on small datasets.

Common Mistakes

  • Expecting a small trim percentage to always remove at least one value, when floor rounding can leave the count at zero on smaller datasets.
  • Choosing a trim percentage close to 50 percent without realizing this behaves almost like reporting the median, discarding most of the actual data.
  • Comparing trimmed means from datasets of very different sizes without accounting for the fact that the effective number of values removed differs even at the same trim percentage.

Edge Cases to Watch For

  • The trim count is rounded down, so small datasets or low trim percentages can result in zero values actually being removed even though a nonzero percentage was requested.
  • If the trim percentage would remove the entire dataset, the calculator returns an error asking you to lower the percentage rather than averaging an empty set.
  • The trim percentage field is capped between 0 and 49 percent, since trimming 50 percent or more from each end would remove the entire dataset in most cases.

Common Use Cases

  • Competition judges scoring events where the highest and lowest scores are conventionally dropped before averaging.
  • Data analysts summarizing measurement data prone to occasional sensor glitches or recording errors.
  • Researchers reporting a robust central tendency alongside the regular mean to show how sensitive results are to extreme values.
Written & fact-checked by the Calculateus TeamLast updated August 5, 2026How we verify our formulas

Frequently asked questions

Why use a trimmed mean instead of the regular mean or median?

A trimmed mean sits between the regular mean (fully sensitive to outliers) and the median (fully ignores magnitude beyond rank) - by dropping a fixed percentage of the most extreme values from each end, it reduces the influence of outliers while still incorporating more information from the bulk of the data than the median alone. This is why it's used in scoring systems like Olympic judging, which trims the highest and lowest scores.

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Conclusion

The Trimmed Mean Calculator gives a middle ground between a mean fully swayed by outliers and a median that ignores most of the data's magnitude. Comparing its output to the regular mean makes clear how much extreme values were affecting the original average.