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Trimmed Mean Calculator

Paste your numbers and choose a trim percentage to get the trimmed mean.

How it is calculated

The engine pulls every number out of the text box (optional minus sign, optional decimal point), sorts them, and counts n. It then removes k = floor(n × p / 100) values from each end, where p is the trim percentage, and averages the rest: trimmed mean = sum of kept values / (n - 2k). The regular mean sum / n is shown beside it, plus the total number of removed values 2k. Because k is rounded down, small lists lose nothing: with 9 numbers and 10%, k = 0 and both means are equal. The trim percentage defaults to 10 when left empty, must be at least 0 and below 50, and separators between numbers can be spaces, commas or new lines.

Worked example

Ten test scores: 12, 15, 14, 13, 16, 15, 14, 95, 13, 12, with a 10% trim. Sorted: 12, 12, 13, 13, 14, 14, 15, 15, 16, 95. The sum is 219, so the regular mean is 219 / 10 = 21.90. Here k = floor(10 × 0.10) = 1, so one value is cut from each end (12 and 95), 2 in total. The remaining eight add up to 112, and 112 / 8 = 14.00. The single outlier of 95 had pulled the plain mean almost eight points up.

Try this example →

Common mistakes

  • Writing decimals with a comma (1,5): the engine reads a number only when it has a dot, so 1,5 is taken as two numbers, 1 and 5, and the result silently changes.
  • Expecting the percentage to be the total trimmed: it is cut from each end, so 10% removes about 20% of the values overall.
  • Trimming a short list and expecting a change: with fewer than 10 values at 10%, nothing is removed because the count is rounded down.
  • Entering a trim of 50 or more, which leaves nothing to average; the tool returns no result.
  • Pasting a column that includes a row number, year or label with digits in it; every number found in the text, including those, goes into the average.

About this calculator

A trimmed mean is a robust measure of central tendency: before averaging, a chosen percentage of the lowest and highest values in the dataset is removed, then the mean is taken of what remains. For example, a 10% trimmed mean drops the bottom 10% and top 10% of sorted values before averaging the middle 80%.

Because a single extreme outlier can drag a regular mean far from where “most” of the data sits, statisticians, economists, and sports judges (figure skating and gymnastics scoring famously trim the highest and lowest scores) use the trimmed mean to get a more representative average that isn't distorted by a handful of unusual values, while still using more information than the median alone.

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