Use the median for a clear summary of the typical sale price in a defined area, period and property group, especially when prices are skewed. Use the arithmetic mean when you need average transaction value, and show it alongside the median to make the effect of high or low sales visible. A trimmed mean can limit the influence of both tails, but only if you state exactly how much data you removed. None of these raw transaction summaries, by itself, measures like-for-like house-price change.
What each measure tells you
Arithmetic mean: average value per transaction
Add the sale prices and divide by the number of transactions. Every recorded sale contributes, so the mean answers an average-per-transaction question. In a market where prices are skewed, a small number of expensive sales can pull it well above the price of a typical sale. The Office for National Statistics (ONS) recommends using mean prices alongside medians to help show the distribution and the effect of very high-value transactions. Mean values and sale counts can also be used to aggregate smaller areas into custom areas; medians cannot simply be combined that way. ONS, House Price Statistics for Small Areas QMI; ONS, House Price Statistics for Small Areas.
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Median: midpoint sale price
Sort the prices and take the middle one. With an even number of sales, a common convention is to take the midpoint of the two central prices. The median is less affected than the mean by an unusually expensive or inexpensive sale, which makes it a useful single summary of a skewed set of property prices. ONS describes the median as its most appropriate average for skewed house-price data. ONS, House Price Statistics for Small Areas QMI.
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Sort the prices, remove a specified proportion from the low end and from the high end, then calculate the mean of what remains. This retains a mean-like summary while reducing the impact of extreme values. The result depends on the trimming rule, so state both tail percentages and how many sales were removed. The reviewed official property-statistics sources do not establish a standard trimming percentage for house prices. NIST, Measures of Location; NIST, Trimmed Mean.
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Choose the measure for the question
| Question | Useful summary | Why and what to watch |
|---|---|---|
| What does a typical sold home cost here? | Median | Less sensitive to a few extreme sales. Define the geography, period, property type and sale population. |
| What is the average transaction value? | Arithmetic mean, usually shown with the median | Every sale counts, but expensive transactions can make the mean unlike the typical sale price. |
| What is a mean-like summary with less influence from unusually high and low prices? | Trimmed mean, checked against the mean and median | Disclose the percentage trimmed from each tail and the number or share of sales removed. No standard property-price trim level is established in the reviewed sources. |
| How has the value of a comparable home or the housing market changed? | A suitable mix-adjusted house-price index | Raw transaction averages can move because the kinds of homes sold changed, not just because like-for-like values changed. |
| What prices matter near the affordable or entry-level end? | Lower quartile or 10th percentile, considered alongside suitable income measures | ONS identifies these percentiles as useful for affordability analysis; the 10th percentile represents the cheaper end of the market. |
Why the mean and median can differ
Imagine five sales: four at £100,000 and one at £1 million. The median is £100,000, while the arithmetic mean is £280,000. The one expensive sale raises the mean without moving the median. The UK government’s simplified example also gives a geometric mean of £158,000; that is a different calculation, not another name for the arithmetic mean. These are figures from the government’s example, not a market estimate. UK government, English Housing Survey 2023 to 2024: Annex table 1.1 methodology.
A higher mean than median can be consistent with a high-price upper tail, but the gap alone does not prove why the measures differ. Check the underlying distribution and which kinds of homes sold before attributing the difference to luxury properties or another cause.
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Use a trimmed mean transparently
- Set the rule before interpreting the result. Specify the percentage removed from the lower tail and the upper tail, and apply it consistently. A symmetric trim removes the same percentage from both; an asymmetric trim needs a substantive reason.
- Report what was removed. Give the trimming percentages and the number or proportion of transactions excluded, so readers can see how much of the data shaped the result.
- Compare the result with the ordinary mean and median. If a conclusion changes depending on the trimming choice, make that sensitivity clear rather than presenting one trimmed value as definitive.
- Investigate bad data rather than silently trimming it away. If a transaction is erroneous, document the data-quality issue. A genuine unusual sale may still be valid and relevant to the market.
NIST describes removing 5% from each tail as a common choice in general location analysis, not as a property-market standard. A 50% trimmed mean—the mean between the lower and upper quartiles—is a much more aggressive trim. Neither convention should be presented as an official house-price method without a source establishing that use. NIST, Measures of Location; NIST, Trimmed Mean.
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Know what transaction prices leave out
The sales observed are not every home’s value
A statistic based on completed sales describes the transactions observed in that period, not the value distribution of all homes, including homes that did not sell. For example, the Department for Levelling Up, Housing and Communities’ 2026 report on its Market Value Survey estimated 2024 values across tenures, rather than reporting completed-sale prices. It gave a mean market value of £348,000 and a median of £275,000 for all dwellings in England. For owner-occupied dwellings, the respective figures were £398,000 and £320,000; for private-rented dwellings, £289,000 and £235,000; and for social-rented dwellings, £218,000 and £180,000. These are rounded values from that survey, not transaction-price summaries. UK government, English Housing Survey 2023 to 2024: Annex table 1.1 methodology.
Changing sales mix can shift raw summaries
If more large detached houses sell in one period and more flats in another, the mean or median may change even when like-for-like values do not. ONS small-area sale-price statistics are not mix-adjusted. For measuring property-value inflation while accounting for changes in property characteristics, use a suitable house-price index rather than treating a raw average as a constant-quality measure. ONS, House Price Statistics for Small Areas; UK government, English Housing Survey 2023 to 2024: Annex table 1.1 methodology.
Geometric means are a separate method
The UK House Price Index uses a weighted geometric mean. Government guidance explains that geometric means give high values less weight than arithmetic means and are usually closer to the median. That choice belongs to the index methodology; it should not be silently substituted for an arithmetic mean when reporting average transaction value. UK government, English Housing Survey 2023 to 2024: Annex table 1.1 methodology.
Small local samples need caution
ONS does not publish its small-area median, mean, lower quartile or 10th percentile for an area-year with fewer than five sales. That is a suppression threshold for this ONS publication, not a universal rule about the minimum sample needed for a reliable estimate. ONS, House Price Statistics for Small Areas QMI.
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When publishing property-price figures, identify the geography and boundary, reference period, property type, transaction population and number of sales. Say whether the data include all residential transactions or a narrower group such as new builds or a particular tenure. ONS House Price Statistics for Small Areas reports price measures and transaction counts by year, geography and property type, though some combinations have limited coverage. ONS, House Price Statistics for Small Areas QMI.
A compact reporting format is: “Among [number] [defined property group] sales in [geography] during [period], the median sale price was [amount] and the arithmetic mean was [amount]. The [percentage from each tail] trimmed mean was [amount], after removing [number or proportion] of sales from each tail. These are transaction-price summaries, not a mix-adjusted estimate of like-for-like price change.” Include an interpretation of the mean–median gap only when the data support it.
For historical context, the same Department for Levelling Up, Housing and Communities report says mean property value rose 41% and median property value rose 45% in nominal terms from 2015 to 2024 in its Market Value Survey series. Those changes apply to that survey’s market-value estimates, not generally to completed-sale prices or a house-price index. UK government, English Housing Survey 2023 to 2024: Annex table 1.1 methodology.
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