Zoho Sheet QUARTILE.INC Function: Inclusive quartiles and inventory thresholds

A quartile marks a position in an ordered distribution. Q1 is the 25th-percentile cutoff, Q2 the midpoint/median and Q3 the 75th-percentile cutoff. The inclusive convention allows minimum and maximum endpoints and linearly interpolates between adjacent observations when a target rank lies between them. The official Zoho help describes this function as based on percentiles from 0 to 1 inclusive; it explicitly equates q=0 with MIN, q=2 with MEDIAN and q=4 with MAX. In the examples below we independently calculate results by the standard inclusive percentile-rank interpolation method, not by running Zoho Sheet.

=QUARTILE.INC(number_list; q)

• number_list (required): the set of numbers to evaluate. A worksheet range such as B2:B9 is the clearest form. The official help example uses A2:A6.
• q (required): which quartile to return: 0 minimum, 1 first quartile (25%), 2 median (50%), 3 third quartile (75%), or 4 maximum. Zoho’s published error table gives #NUM! when q falls outside 0–4. For reliable portability, use integer values 0, 1, 2, 3 or 4; do not assume fractional-q coercion without testing.

Unlike the plain PERCENTILE.INC function, this argument is a quartile index, not the decimal fraction 0.25 or 0.75. For example, QUARTILE.INC(range;1) corresponds to an inclusive 25th percentile; PERCENTILE.INC(range;0.25) uses a fractional percentile parameter.

Create a blank worksheet and enter the following data in A1:B9. Do not sort it for a function to work; we deliberately list the quantities in ascending order so that manual calculations are easy to audit.

These values are hypothetical. Eight observations are convenient for learning, but production decisions need larger, representative samples. Quartiles describe the distribution of numeric observations, not which individual product is best or worst. If the observations have very different importance (for example one represents one sale and another represents a million sales), this unweighted calculation may be unsuitable.

1. Enter the sample data in A1:B9, keeping the quantity column numeric.
2. In D2 enter =QUARTILE.INC(B2:B9;0). Expected 4 (smallest quantity).
3. In D3 enter =QUARTILE.INC(B2:B9;1). Expected 11 (Q1).
4. In D4 enter =QUARTILE.INC(B2:B9;2). Expected 18 (median).
5. In D5 enter =QUARTILE.INC(B2:B9;3). Expected 25 (Q3).
6. In D6 enter =QUARTILE.INC(B2:B9;4). Expected 32 (largest quantity).

Why Q1 is 11 rather than 8 or 12: With eight sorted observations, the standard inclusive 25th-percentile rank is 1+(8-1)*0.25 = 2.75. The second value is 8 and the third is 12. Three-quarters of the way between them gives 8+0.75*(12-8)=11. At 75% the rank is 6.25, yielding 24+0.25*(28-24)=25. Those calculations are a transparent manual explanation of the expected values; they are not execution evidence from Zoho.

An analyst might use interquartile range (IQR) to measure typical spread while reducing the influence of extreme observations. In D8 enter:

=QUARTILE.INC(B2:B9;3)-QUARTILE.INC(B2:B9;1)

Expected output: 25-11 = 14 units. Unlike maximum minus minimum (here 32-4 = 28), IQR summarizes the middle half of the distribution. It does not tell you total warehouse inventory: use SUM for that task.

To flag individual low-stock products relative to the dataset, enter in C2 and copy down:

=IF(B2<QUARTILE.INC($B$2:$B$9;1);"Below Q1";"At/above Q1")

Expected C2 for four units: Below Q1; expected C3 for eight units: Below Q1; expected C4 for twelve units: At/above Q1. Absolute range anchors $B$2:$B$9 keep the benchmark fixed when the formula is copied. This is a relative rule: if all eight products have too little stock, a quartile-based flag can fail to catch absolute shortages. Combine it with a business minimum-reorder threshold.

A Tukey-style exploratory lower fence is Q1-1.5*IQR = 11-21 = -10 and upper fence is Q3+1.5*IQR = 25+21 = 46. The sample has no observations outside these calculated fences. Such fences are descriptive heuristics, not automatic evidence that an inventory record is erroneous.

For the same eight values, the standard exclusive method calculates Q1=9, Q2=18 and Q3=27; that is different from this guide’s inclusive 11, 18, 25. Use a consistent method when publishing percentiles or comparing departments. Excel provides QUARTILE.INC and QUARTILE.EXC; its formula examples normally show comma-separated arguments in English-language documentation. Zoho’s official reference uses semicolons. Google Sheets also offers quartile functions, but do not assume every coercion rule, boundary error or platform release matches Zoho simply because the name matches. Differences here are documented conceptually and computed independently; native Zoho edge-case execution remains pending.

For older spreadsheets, QUARTILE is documented by Zoho as a legacy function superseded by QUARTILE.INC; do not change saved workbooks without comparing actual outputs and preserving the original formulas. For an exact observed minimum/maximum, MIN or MAX communicates the intent more directly than q=0 or q=4.

Check the number range first. A header or a copied extra row can change the result. Use B2:B9, not B1:B9, for the practice dataset. A completely empty numerical input is documented as a possible #NUM! situation. If all values are text, first convert intended numbers to actual numeric cell values. The vendor’s general error table also lists #VALUE! for wrong argument types, #REF! for invalid references and #NAME! for an invalid function name. Which error appears for every mixed-data coercion is not verified by this guide.

Understand ties and repeated rows. Two identical quantities count as two observations; that is usually correct for two different products. De-duplicating values changes the distribution and is normally inappropriate. Negative inventory balances should be investigated rather than silently excluded; a quartile can legitimately be negative if negative numbers were intentionally supplied.

Check the intended definition of a quartile. Different statistical systems and textbooks use different conventions for interpolating observations. A quartile from one convention should not be compared to a published benchmark using another without identifying its method. A quartile is a distribution summary, not a prediction or an exact count of records below it—especially with repeated values.

Troubleshoot a surprise result methodically. First enter a literal 1, 2 or 3 for q. Then verify every input cell is numeric; evaluate the sample data exactly as shown; compare inclusive and exclusive results; and finally test any unusual edge case in your own Zoho Sheet account. Do not treat the independent Python calculations in this guide as proof that a particular Zoho account, language setting, desktop release or mobile application behaves identically.

The function appears in Zoho’s public Sheet function-reference catalogue and its individual help article was checked October 12, 2026. The retrieved article does not supply a dependable first-supported release date, complete platform matrix, tenant rollout requirements or a promise of behavior across all offline clients. Therefore, this guide does not invent a version number or assert support on every device. Syntax shown uses the semicolon argument separator in Zoho’s published help; locale or editing mode can affect separators in an actual workbook. Validate the formula directly in the version and environment used by your team before depending on it.

• MEDIAN — the middle observation
• PERCENTILE.INC — inclusive percentile thresholds
• PERCENTILE.EXC — exclusive percentile thresholds
• COUNTIF — count records meeting a threshold

Authoritative function reference: Zoho Sheet function help (checked October 12, 2026). Catalogue comparison: Zoho Sheet functions catalogue.

Verification status: Official documentation checked; interpolation and example outcomes independently calculated. Not executed in Zoho Sheet. No genuine application screenshots are included; no mock application images are used. Native runtime and exceptional-input behavior remain unverified.

The official Zoho QUARTILE.INC page explicitly lists the minimum/median/maximum equivalences and a #NUM! warning for out-of-range q. The statistical explanation here uses ordinary linear interpolation for interpretability; native run not performed.