Excel PERCENTILE and QUARTILE Functions
last modified April 4, 2025
The PERCENTILE
and QUARTILE
functions are powerful
statistical tools in Excel. They help analyze data distribution by finding
values at specific percentiles or quartiles. This tutorial provides a
comprehensive guide to using these functions. You'll learn their syntax,
differences, and practical applications with detailed examples.
PERCENTILE/QUARTILE Basics
PERCENTILE
returns the value at a specific percentile in a dataset.
QUARTILE
is a special case that returns values at the 0%, 25%,
50%, 75%, and 100% points. Both help understand data distribution.
Function | Description |
---|---|
PERCENTILE | Returns value at given percentile (0-1) |
PERCENTILE.INC | Inclusive version (Excel 2010+) |
PERCENTILE.EXC | Exclusive version (Excel 2010+) |
QUARTILE | Returns value at quartile (0-4) |
QUARTILE.INC | Inclusive version (Excel 2010+) |
QUARTILE.EXC | Exclusive version (Excel 2010+) |
This table shows the different variations of these functions. The .INC versions include 0 and 1 percentiles, while .EXC versions exclude them. QUARTILE is essentially PERCENTILE for specific points (0%, 25%, 50%, 75%, 100%).
Basic PERCENTILE Example
This example demonstrates finding the 90th percentile in a dataset of test scores. The percentile shows the score below which 90% of scores fall.
A | B |
---|---|
78 | |
85 | |
92 | |
88 | |
95 | |
=PERCENTILE.INC(A1:A5, 0.9) |
=PERCENTILE.INC(A1:A5, 0.9)
This formula calculates the 90th percentile of test scores in A1:A5. The result will be approximately 93.8, meaning 90% of scores are below this value. The .INC version includes the 0th and 100th percentiles in calculations.
QUARTILE Example with Sales Data
This example uses QUARTILE to analyze quarterly sales data distribution. It shows how to find all five quartile points (minimum, Q1, median, Q3, maximum).
A | B |
---|---|
12500 | |
18700 | |
14300 | |
21000 | |
16500 | |
=QUARTILE.INC(A1:A5, 0) | |
=QUARTILE.INC(A1:A5, 1) | |
=QUARTILE.INC(A1:A5, 2) | |
=QUARTILE.INC(A1:A5, 3) | |
=QUARTILE.INC(A1:A5, 4) |
=QUARTILE.INC(A1:A5, 0) // Minimum =QUARTILE.INC(A1:A5, 1) // First quartile (25%) =QUARTILE.INC(A1:A5, 2) // Median (50%) =QUARTILE.INC(A1:A5, 3) // Third quartile (75%) =QUARTILE.INC(A1:A5, 4) // Maximum
These formulas calculate all five quartile points for the sales data. Quartile 0 is the minimum (12500), Q1 is ~14400, median is 16500, Q3 is ~19600, and Q4 is the maximum (21000). This gives a complete picture of data distribution.
PERCENTILE.EXC vs PERCENTILE.INC
This example demonstrates the difference between the inclusive and exclusive versions of PERCENTILE. The .EXC version excludes 0% and 100% percentiles.
A | B | C |
---|---|---|
15 | =PERCENTILE.INC(A1:A5, 0) | =PERCENTILE.EXC(A1:A5, 0) |
22 | =PERCENTILE.INC(A1:A5, 0.5) | =PERCENTILE.EXC(A1:A5, 0.5) |
30 | =PERCENTILE.INC(A1:A5, 1) | =PERCENTILE.EXC(A1:A5, 1) |
18 | ||
25 |
=PERCENTILE.INC(A1:A5, 0) // Returns 15 (minimum) =PERCENTILE.EXC(A1:A5, 0) // Returns #NUM! error =PERCENTILE.INC(A1:A5, 1) // Returns 30 (maximum) =PERCENTILE.EXC(A1:A5, 1) // Returns #NUM! error
The .INC version works with 0 and 1 percentiles, returning min/max values. The .EXC version returns errors for these cases as it excludes extremes. For 0.5 (median), both return similar values (~23.5 in this case).
Using QUARTILE for Outlier Detection
This example shows how to use QUARTILE to identify potential outliers using the interquartile range (IQR) method. IQR is Q3-Q1, and outliers are typically values below Q1-1.5*IQR or above Q3+1.5*IQR.
A | B |
---|---|
12 | =QUARTILE.INC(A1:A10,1) |
15 | =QUARTILE.INC(A1:A10,3) |
18 | =B1-1.5*(B2-B1) |
20 | =B2+1.5*(B2-B1) |
22 | |
25 | |
28 | |
32 | |
35 | |
120 |
=QUARTILE.INC(A1:A10,1) // Q1 (18) =QUARTILE.INC(A1:A10,3) // Q3 (32) =B1-1.5*(B2-B1) // Lower bound (-3) =B2+1.5*(B2-B1) // Upper bound (53)
This calculates Q1 (18) and Q3 (32), then determines outlier thresholds. The value 120 exceeds the upper bound (53), identifying it as a potential outlier. This method is commonly used in statistical analysis.
PERCENTILE with Conditional Data
This advanced example combines PERCENTILE with FILTER to calculate percentiles for specific subsets of data. Here we find the 75th percentile for sales in the East region only.
A (Region) | B (Sales) | C |
---|---|---|
East | 12000 | |
West | 15000 | |
East | 18000 | |
North | 9000 | |
East | 21000 | |
=PERCENTILE.INC(FILTER(B1:B5,A1:A5="East"),0.75) |
=PERCENTILE.INC(FILTER(B1:B5,A1:A5="East"),0.75)
This formula first filters to only East region sales (12000, 18000, 21000), then calculates the 75th percentile (~19500). This technique is powerful for analyzing specific segments within larger datasets.
The PERCENTILE
and QUARTILE
functions are essential
for statistical analysis in Excel. They help understand data distribution,
identify outliers, and compare subsets. Remember that .INC includes min/max
while .EXC excludes them. Mastering these functions provides valuable insights
into your data's characteristics.
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