QUARTILE in WPS Spreadsheet: Build a Five-Number Summary and Explain Cutoffs
Use WPS QUARTILE selectors 0 through 4, check the median and endpoints, and distinguish quartile values from equal-size record groups.
Verification status: See the evidence and test scope described in this guide. How formula examples are checked
Quick answer: QUARTILE returns a selected value from a five-number summary: minimum, first quartile, median, third quartile or maximum. The selector is 0, 1, 2, 3 or 4, not a percentage such as 25 or 75.
Availability and version history
- Introduced: documented by 2019-05-20 in an official WPS lesson; the first release is not established.
- Availability: the lessons identify WPS Office for Windows Personal, without a numeric build range.
- Scope: exact current supported builds and other WPS clients remain unverified; historical documentation does not establish retirement.
- Checked: October 14, 2026 against function-specific sources. Worked results were independently calculated; no native WPS test was performed.
Syntax and documented selectors
=QUARTILE(array, quart)
Both arguments are required. The official lesson’s selector image maps the argument as follows:
| quart | Meaning |
|---|---|
| 0 | Minimum |
| 1 | First quartile, 25% point |
| 2 | Median, 50% point |
| 3 | Third quartile, 75% point |
| 4 | Maximum |
The lesson says noninteger selectors are truncated, and its walkthrough identifies out-of-range selectors as #NUM!. Its formal text has a broken invalid-selector line; the walkthrough separately supplies the range 0–4. A missing argument, an empty cell reference and an explicit zero are not assumed to be interchangeable.
The full interpolation algorithm is not stated in this source. The primary fixture deliberately repeats values around the quartile positions; it is not a certification of every small-sample interpolation convention.
Example 1: construct a complete summary
Enter these nine numeric observations in A2:A10:
10, 20, 20, 20, 50, 80, 80, 80, 90
Enter selectors 0, 1, 2, 3 and 4 in C2:C6. In D2 enter and fill through D6:
=QUARTILE($A$2:$A$10,C2)
The independently calculated expected summary is:
| Selector | Expected value |
|---|---|
| 0 | 10 |
| 1 | 20 |
| 2 | 50 |
| 3 | 80 |
| 4 | 90 |
The anchored reference keeps all nine observations in every calculation. The selector changes as the formula is filled. Place the summary outside A2:A10 so it cannot become part of its own source dataset.
Example 2: verify three selectors separately
For the same dataset:
=MIN(A2:A10)
=MEDIAN(A2:A10)
=MAX(A2:A10)
Expected results are 10, 50 and 90, matching QUARTILE selectors 0, 2 and 4. These three equivalences are explicitly stated in the WPS lesson.
The source’s truncation rule gives =QUARTILE(A2:A10,2.9) the same expected result as selector 2: 50. Use an explicit integer selector in normal work so truncation does not conceal a mistaken input.
Advanced example: tied cutoffs do not divide rows evenly
The first quartile is 20. Four of the nine observations are less than or equal to 20: 10, 20, 20 and 20. Thus a rule that includes every observation at or below Q1 selects 4/9, approximately 44.44%, of the rows, not exactly 25%.
Similarly, four observations are at or above Q3=80. Repeated boundary values can prevent quartile cutoffs from producing four equal-size groups of records.
A quartile is a numeric threshold. Assigning records to groups also needs explicit boundary and tie rules. Do not silently split identical measurements merely to force equal group sizes.
Advanced example: a transparent interquartile-range check
For the primary fixture, the independent interquartile range is Q3-Q1 = 80-20 = 60. Using a separately chosen 1.5-IQR screening rule produces lower and upper fences:
20-1.5*60 = -70 and 80+1.5*60 = 170.
These fences are a statistical screening policy, not an automatic operation performed by QUARTILE. All nine original observations fall between them.
To assess a new value 200 against this fixed reference summary, compare it with 170; it exceeds the upper fence. Adding 200 into the reference dataset and recalculating would be a different analysis, potentially changing the quartiles and fences themselves.
Units, missing data and source limits
For a positive scale change, multiplying the primary observations by ten yields an independently expected summary 100, 200, 500, 800 and 900. The IQR becomes 600. Quartiles and their differences carry the measurement units of the input.
The lesson explicitly documents #NUM! for an empty array. It does not provide a complete rule for mixed text, Boolean, error and blank-reference inputs; keep primary examples numeric rather than borrowing another spreadsheet’s coercion policy.
MEDIAN, MIN and MAX provide useful endpoint and center checks. Current-build interpolation details and exact treatment of a blank selector remain unverified.
References and verification
- WPS Academy: QUARTILE, 2019-05-20 (Chinese; Windows Personal).
- Editorial testing standards.
Expected outputs are independent calculations, not recorded native results. Current-build limits beyond the cited documentation remain unverified.