PERCENTILE.INC function

Returns the value at a specified percentile (0–100%) of a dataset using linear interpolation for in-between values.

=PERCENTILE.INC(array, k)

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Arguments

How PERCENTILE.INC reads its arguments
arrayrequiredkrequiredPERCENTILE.INC
ArgumentRequiredDescription
arrayRequiredA range or array of numeric values. If empty or contains only text, returns an error. Mixed text and numbers are handled by ignoring non-numeric entries.
kRequiredA number between 0 and 1 (inclusive) representing the percentile. k=0 returns the minimum, k=1 returns the maximum, k=0.5 returns the median.

Returns

A numeric value representing the k-th percentile of the array.

Availability

Excel: All · Google Sheets: Supported

Worked examples

1. Find the 25th percentile of list prices (bottom quarter)

AddressBedsBathsList PriceDays on Market
123 Oak St3245000015
456 Maple Ave436250008
789 Pine Rd2132500032
321 Elm Dr3247500012
654 Birch Ln548500005
=PERCENTILE.INC(D2:D6, 0.25)

Result: 450000

The 25th percentile divides the lowest quarter of prices from the rest. When the five list prices are sorted (325000, 450000, 475000, 625000, 850000), the 25th percentile lands at 450000. This tells a real estate agent that one quarter of homes in this market sell below this price point.

2. Find the median days on market (50th percentile)

AddressBedsBathsList PriceDays on Market
123 Oak St3245000015
456 Maple Ave436250008
789 Pine Rd2132500032
321 Elm Dr3247500012
654 Birch Ln548500005
=PERCENTILE.INC(E2:E6, 0.5)

Result: 12

The 50th percentile is the median—the middle value. Days on market sorted are [5, 8, 12, 15, 32], so 12 is at the center. This means half of these properties sold in 12 days or fewer, and half took longer. It's a useful benchmark for expected selling speed.

3. Find the 90th percentile of prices (top 10% threshold)

AddressBedsBathsList PriceDays on Market
123 Oak St3245000015
456 Maple Ave436250008
789 Pine Rd2132500032
321 Elm Dr3247500012
654 Birch Ln548500005
=PERCENTILE.INC(D2:D6, 0.9)

Result: 760000

The 90th percentile identifies the price threshold for luxury homes. PERCENTILE.INC interpolates between the 4th value (625000) and 5th value (850000) to land at exactly 760000. Homes priced above this point represent the top 10% most expensive listings in the dataset.

Common errors

Which PERCENTILE.INC error are you seeing?
PERCENTILE.INC returned an error#NUM!
Convert your percentile to a decimal between 0 and 1. For the 75th percentile, use k=0.75; for the 30th, use k=0.30. Do not use k=75 or k=1.5.
#VALUE!
Ensure k is a decimal number, not a percentage formatted as text. Convert text percentages before use: if B1 contains '50%', use =PERCENTILE.INC(array, B1/100) or =PERCENTILE.INC(array, 0.5) directly.
#REF!
Verify the array range exists in the current workbook. Re-select the range in your formula or create a named range for the data if you plan to move or reorganize the sheet later.
ErrorWhy it happensHow to fix it
#NUM!The k value is less than 0 or greater than 1. PERCENTILE.INC requires k to represent a valid percentile between the minimum and maximum of your dataset.Convert your percentile to a decimal between 0 and 1. For the 75th percentile, use k=0.75; for the 30th, use k=0.30. Do not use k=75 or k=1.5.
#VALUE!The array contains text or other non-numeric data that cannot be evaluated, or k is text instead of a number (for example, k='50%' instead of 0.5).Ensure k is a decimal number, not a percentage formatted as text. Convert text percentages before use: if B1 contains '50%', use =PERCENTILE.INC(array, B1/100) or =PERCENTILE.INC(array, 0.5) directly.
#REF!The array range references cells that no longer exist, have been deleted, or are in a closed or unavailable workbook. For example, =PERCENTILE.INC(A1:A100, 0.5) breaks if columns A is deleted or the source sheet is removed.Verify the array range exists in the current workbook. Re-select the range in your formula or create a named range for the data if you plan to move or reorganize the sheet later.

Tips and when to use something else

  • PERCENTILE.INC includes k=0 (minimum) and k=1 (maximum) as valid inputs, making it inclusive. Use PERCENTILE.EXC for the exclusive version that excludes extreme values from calculation.
  • MAX and MIN are special cases: PERCENTILE.INC(..., 0) equals MIN(array) and PERCENTILE.INC(..., 1) equals MAX(array). For k between 0 and 1, the result is interpolated.
  • Use LARGE(array, 1) or SMALL(array, 1) when you need an exact rank (the 5th largest value), but use PERCENTILE.INC when you need a threshold that divides your data by percentage.
  • PERCENTILE.INC works with any distribution—uniform, skewed, or irregular—without assuming normality. It's a distribution-free statistic, making it robust for real-world messy data.

Frequently asked questions

How do I convert a percentage (like 75%) into the k value PERCENTILE.INC needs?
Divide the percentage by 100. The 75th percentile uses k=0.75, the 30th uses k=0.30. If you have a cell with the text '75%', use =PERCENTILE.INC(array, value/100) to convert it, or manually enter 0.75.
Why does PERCENTILE.INC return a decimal when all my data is whole numbers?
PERCENTILE.INC interpolates linearly between data points when k falls between two values. For example, the 90th percentile of [1, 2, 3, 4, 5] returns 4.6 (between 4 and 5), not 5. This interpolation gives a more statistically accurate result than rounding to the nearest data point.
Can PERCENTILE.INC handle data that isn't normally distributed?
Yes, absolutely. PERCENTILE.INC is distribution-free—it works with any shape of data: uniform, skewed, bimodal, or irregular. It simply finds the position that splits your data at a given percentage, regardless of distribution shape.
What's the difference between PERCENTILE.INC and PERCENTILE.EXC?
PERCENTILE.INC (inclusive) accepts k from 0 to 1, where k=0 gives the minimum and k=1 gives the maximum. PERCENTILE.EXC (exclusive) only accepts k strictly between 0 and 1, excluding the endpoints. Use PERCENTILE.INC for most analyses unless you specifically want to exclude min/max values.

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Reviewed 2026-09-17