INTERCEPT Function in Calligra Sheets: Regression Examples

INTERCEPT returns the fitted y value when x = 0 for an ordinary least-squares straight line through paired numeric observations. This is the constant term b in the model y = mx + b, where m is given by SLOPE.

=INTERCEPT(B2:B6;A2:A6)

With the sample below, the independently calculated expected intercept is 0.9, and the separately calculated slope is 1.1. Neither number was obtained by actually executing Calligra Sheets.

=INTERCEPT(y;x)

• y (first, required): dependent numeric observations supplied as a range/array (B2:B6).
• x (second, required): independent numeric observations matched to y point by point (A2:A6).
• Result: a single floating-point y-axis intercept b = average(y) − slope(y;x) × average(x) when the slope is defined.
• Required arguments: exactly two (setParamCount(2)); arrays/ranges accepted (setAcceptArray()).
• Optional arguments/defaults: none in pinned KDE registration and XML.
• Watch the order: as with SLOPE, y goes first; reversed arguments describe a different regression model.

This matches INTERCEPT(y;x) in KDE’s official function handbook, the KDE XML specification, and the 26.08.2 C++ registration. The implementation explicitly calculates mean(y) minus slope times mean(x), with the same kind of count checks found in SLOPE.

On a new sheet, enter these numbers in A1:G6. Row 1 is text labels; rows 2–6 are numeric. Keep the results outside this input area (for example in I2 and below). The helper columns deliberately transform the same pairs so you can check whether a formula responds as expected.

Each row is one paired observation: A2 corresponds to B2, A3 to B3, and so on. Never sort one measurement column without sorting its paired column. Use a period as the decimal separator only in a locale configured for that convention. The formulas below use the semicolon (;) separator shown in KDE’s English-language function documentation; localized applications may use a different display/entry convention.

To reproduce a row in any example table, click an unused result cell, type the formula beginning with =, press Enter, and compare its display to the independently calculated expected value. Increase displayed decimal places when checking precision. The numerical values in this guide were not obtained from running Calligra Sheets.

All outputs are independent mathematical expectations, not Calligra-run observations. An intercept is a model parameter; it is not necessarily a y value measured in the source data.

Manual derivation: x̄=3, ȳ=4.2, Sxy=11, Sxx=10. So slope m = 11/10 = 1.1, and b = 4.2 − 1.1 × 3 = 0.9. The predicted y at x=6 is 0.9 + 1.1×6 = 7.5. Mathematical identities were checked independently, not in the app.

Imagine A2:A6 are machine operating hours and B2:B6 are the corresponding measured energy-use units in a deliberately simplified experiment. A line of the form energy ≈ fixed baseline + variable consumption × hours gives the intercept a natural interpretation: the fitted baseline at zero operating hours, subject to real-world model assumptions.

Choose cells I2:I5 and enter:

I2: =INTERCEPT($B$2:$B$6;$A$2:$A$6)
I3: =SLOPE($B$2:$B$6;$A$2:$A$6)
H4: 0
I4: =$I$2+$I$3*H4
H5: 6
I5: =$I$2+$I$3*H5

Expected I2=0.9, I3=1.1, I4=0.9, I5=7.5. The zero-hours estimate (0.9) is a regression extrapolation if observations start at one hour; don’t interpret it as a physically confirmed standing load without measurements near zero. The six-hours estimate is also outside the example’s x range (1–5).

For a second independent check (not relying on INTERCEPT itself), use:

=AVERAGE(B2:B6)-COVAR(A2:A6;B2:B6)/VARP(A2:A6)*AVERAGE(A2:A6)

Expected output 0.9 under the documented population-covariance and population-variance definitions. This identity is mathematically equivalent to the source implementation for the five nonmissing numeric pairs; it has not been evaluated in Calligra.

• All x values identical: x variation is zero, so a unique slope and intercept cannot be determined from x-only constant data. Source calculates division by the zero squared-deviation sum; the visible Calligra error string requires native checking.
• All y values identical with varying x: the fitted line is flat, slope 0, intercept the constant y. The helper G column makes this case testable without uncertainty about missing values.
• Empty or different-size numeric data: C++ checks count(args[0]), count(args[1]) and returns an internal value error on unequal counts or fewer than one numeric item. Exactly how it treats text, Boolean values or blanks is not proven by this formula-only review.
• Reversed arguments: INTERCEPT(x;y) estimates x from y; it is not the same as estimating y from x.
• Units and interpretation: the intercept has units of y, while SLOPE has units y/x. An intercept far outside observed x can be practically meaningless even when computable.
• Outliers and nonlinearity: least-squares models are affected by outliers and cannot safely represent all trends.
• Zero observations not measured: a fitted intercept may be nonzero even if the measured y series never included x=0.

Shared troubleshooting checklist

1. Confirm the entered formula begins with = and the function name is spelled exactly as shown.
2. Follow the KDE semicolon syntax when using an English-style installation (; rather than Excel’s common ,). See KDE’s formula-entry guidance; adjust for your application’s locale where necessary.
3. Ensure both ranges represent the same observations in matching row order; the example uses five numeric points, not five random numbers from separate contexts.
4. Check for numbers stored as text, blank cells, Boolean values and nonnumeric entries. The handbook/source do not establish all native pair-exclusion and coercion cases tested here; normalize source data or validate them in your installed build.
5. Check for constant or nearly constant series. Correlation and regression denominators can be zero or poorly conditioned.
6. If the result is visibly rounded, increase displayed decimal places before judging it incorrect. Floating-point arithmetic can produce tiny rounding differences.
7. For a parsing failure, inspect argument separators and region-specific decimal characters before changing formula logic.
8. For an unexpected error from a range, try the five-number all-numeric reproduction above, then restore your actual data one cell at a time. Do not assume a particular error label without a native test.

Microsoft’s INTERCEPT documentation uses INTERCEPT(known_y's, known_x's) (comma between inputs in English-language Excel); KDE shows INTERCEPT(y;x) (semicolon). These represent the same standard regression concept and argument order, but no Excel workbook import/export, platform comparison, locale conversion or visible error handling was tested. Microsoft’s detailed handling of ignored text, blanks or mismatched pairs is Excel-specific documentation, not direct evidence of Calligra behavior.

• KDE INTERCEPT, SLOPE, CORREL, COVAR, AVERAGE, VARP.
• KDE version-pinned registration, KDE version-pinned implementation, statistical function XML and formula entry rules.
• Microsoft INTERCEPT documentation — Excel-only comparison.

Research snapshot: KDE Gear / Calligra 26.08.2 (released October 8, 2026); checked October 13, 2026. The KDE application release listing identifies 26.08.2 as the current release on the checked date, and KDE’s release announcement records the release date. The handbook is a useful syntax reference but is not itself proof that every old handbook example matches every modern binary. This guide also compares the exact 72123cc643f6625351139e7df294544255a1056f source revision.

Platform: The cited upstream release and package information concerns Calligra primarily distributed for Linux, including distribution packages and Flathub. Which function is available in your installed binary depends on its package, version and enabled modules. We did not test Windows, macOS, mobile, or individual distribution builds, so this page does not certify identical results on those platforms.

Validation labels: OFFICIAL_DOCUMENTATION_CHECKED = described by KDE’s documentation/XML; SOURCE_LOGIC_INSPECTED = the named functions and argument counts were found in the pinned C++ source; INDEPENDENT_ARITHMETIC = output computed using ordinary mathematics outside Calligra; NATIVE_CALLIGRA_EXECUTION_NOT_RUN = no actual Calligra spreadsheet, screenshot, error dialog, or imported Excel workbook was tested. Treat boundary cases specifically marked unverified as test cases, not promised visible outputs.