What it means
An ordinary average treats every number equally, which means one unusually large or small figure can pull it a long way. If nine deals are worth about $45,000 and one is worth $115,000, the simple average gives a misleading idea of a typical deal.
Trimming removes such extremes before averaging. To calculate it, you first choose how much to trim from each end, such as 10% or 20%.
You sort the data, drop that share from the bottom and top, and take the ordinary average of what remains. A 10% trimmed mean on ten values removes the lowest one and the highest one.
The method is common wherever outliers are expected. Economists use trimmed measures to read inflation more clearly by ignoring the biggest price swings, sports judges drop the top and bottom scores, and finance teams use them when assessing sales, expenses or valuation multiples across a group of similar companies.
The choice of trimming percentage is a judgement call. Trimming too little leaves the outliers in place, while trimming too much throws away real information and moves the answer towards the median.
A figure of 5% to 20% from each end is typical. One important point is that trimming is not the same as deleting errors.
If a figure is wrong, it should be corrected or excluded for that reason, whereas a trimmed mean removes genuine but extreme values on purpose, and that choice should be disclosed. A related idea is the winsorised mean, which replaces the extreme values with the nearest remaining value instead of dropping them.
Both methods aim to reduce the influence of outliers, and the choice between them depends on whether you want to discard extreme observations or merely limit how much they can count.
In practice
Real-world examples.
Example
A sales director reviews ten regional managers' quarterly revenue and finds one who landed an exceptional contract. She reports a 10% trimmed mean alongside the ordinary average, so the board sees typical performance and not just the star.
Example
A central bank analyst tracks inflation by removing the 15% of price categories with the biggest rises and the 15% with the biggest falls each month. The resulting measure moves less sharply than the headline figure and helps show the underlying trend.
Example
An investment analyst values a software company using the price-to-sales multiples of twelve peers. She drops the highest and lowest multiple before averaging, because one peer is under takeover offer and another is in distress.
Formula
Calculation
Trimmed mean = Sum of the values left after trimming / Number of values left after trimming
A sales team has ten deal sizes, in thousands of dollars: 5, 40, 42, 44, 45, 46, 47, 48, 48, 115. The ordinary mean is (5 + 40 + 42 + 44 + 45 + 46 + 47 + 48 + 48 + 115) / 10 = 480 / 10 = $48,000.
A 10% trimmed mean removes one value from each end, the 5 and the 115, leaving 40, 42, 44, 45, 46, 47, 48 and 48. Their sum is 360, and there are 8 values, so the trimmed mean is 360 / 8 = $45,000. The median is (45 + 46) / 2 = $45,500, so the trimmed mean sits close to the typical deal while the ordinary mean is pulled up by the $115,000 outlier.Case study
Seen in the real world.
Larkfield Foods is an illustrative, fictional grocery distributor that tracked delivery cost per order across 200 routes. The simple average of $38 looked fine, but the operations manager noticed that a handful of emergency deliveries cost over $300 each.
Finance calculated a 10% trimmed mean, removing the 20 cheapest and 20 dearest routes, and got $31. This showed that a normal route cost about $7 less than the headline average suggested.
The illustrative lesson is that a single average rarely tells the whole story, and Larkfield now reports both figures. The trimmed mean guides pricing for regular customers, while the ordinary mean, which includes the emergencies, is used to check the total budget.
Watch out
Common mistakes.
- Trimming only one end of the data, which biases the result up or down.
- Choosing the trimming percentage after seeing which answer looks best, instead of fixing it in advance.
- Using a trimmed mean to hide genuine extreme costs, when the total budget still has to include them.
Questions
People also ask.
What is the difference between a trimmed mean and a median?
The median is the middle value only, whereas the trimmed mean averages all values left after trimming, so it uses more of the data.
How much should I trim?
Between 5% and 20% from each end is common, and the figure should be stated whenever the result is reported.
Is it better than the ordinary mean?
It is better for describing a typical value when outliers are present, but the ordinary mean is the right choice for totals.
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