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INTERCEPT Function (LibreOffice Calc)

Math Beginner LibreOffice Calc Introduction not established

The INTERCEPT function in LibreOffice Calc returns the Y-intercept of the linear regression line through a set of data points. This guide explains syntax, examples, regression logic, errors, and best practices.

Verification status: Consult the documentation, examples and any stated test scope below. How formula examples are checked

Availability and version history

  • Introduced: Documented by LibreOffice 26.8.1.1; original introduction not established.
  • Availability: Supported in LibreOffice 26.8.1.1, verified against its function registry. This identifies a supported release, not a final working version.
  • Scope: Desktop Calc, using the English function name. Availability in other spreadsheet applications is separate.
  • Checked: 2026-10-14 — function reference; versioned support. Documentation/source check; not a new native test. Existing example-specific test claims below retain their stated scope.
The **INTERCEPT** function returns the **Y-intercept (b)** of the best-fit linear regression line through a set of data points. It is one of the core components of linear modeling in Calc and is used internally by FORECAST, TREND, and LINEST.

What the INTERCEPT Function Does

  • Calculates the Y-intercept of the regression line
  • Uses least-squares linear regression
  • Works with numeric X/Y pairs
  • Useful for forecasting, trend analysis, and modeling
  • Works across sheets

The regression line is:

y = m*x + b

INTERCEPT returns b.

Syntax

INTERCEPT(known_y; known_x)

Where:

  • known_y — dependent variable (Y values)
  • known_x — independent variable (X values)
X and Y ranges must be the same size.

Basic Examples

Intercept of Y vs X

=INTERCEPT(B1:B10; A1:A10)

Intercept across sheets

=INTERCEPT(Sheet1.B1:B50; Sheet2.A1:A50)

Intercept using named ranges

=INTERCEPT(Sales; Months)

Intercept with dates as X-values

=INTERCEPT(B1:B100; A1:A100)

(Calc automatically converts dates to serial numbers.)

Advanced Examples

Manual FORECAST equivalent using SLOPE + INTERCEPT

=SLOPE(B1:B10; A1:A10) * 11 + INTERCEPT(B1:B10; A1:A10)

Intercept ignoring errors

=INTERCEPT(IF(ISNUMBER(B1:B10); B1:B10); A1:A10)

(Confirm with Ctrl+Shift+Enter in older Calc.)

Intercept using filtered (visible) data only

Use SUBTOTAL helper column to filter X/Y before passing to INTERCEPT.

Intercept after removing outliers

=INTERCEPT(FILTER(B1:B100; B1:B100<1000); FILTER(A1:A100; B1:B100<1000))

Intercept for time-series forecasting

=INTERCEPT(Sales; Dates)

Intercept for normalized data

=INTERCEPT((B1:B10 - AVERAGE(B1:B10)); (A1:A10 - AVERAGE(A1:A10)))

How INTERCEPT Calculates the Regression Constant

INTERCEPT uses the least-squares formula:

[ b = \bar{y} - m \cdot \bar{x} ]

Where:

  • ( m ) = slope (from SLOPE or LINEST)
  • ( \bar{x} ) = mean of X
  • ( \bar{y} ) = mean of Y

This is the same intercept used by LINEST, TREND, and FORECAST.

Common Errors and Fixes

Err:502 — Invalid argument

Occurs when:

  • X and Y ranges have different sizes
  • Non-numeric text included
  • One of the ranges is empty

Err:504 — Parameter error

Occurs when:

  • Semicolons are incorrect
  • Range references malformed

INTERCEPT returns unexpected value

Possible causes:

  • Relationship is not linear
  • Outliers distort regression
  • X-values not aligned with Y-values
  • X-values have zero variance (all X are identical)

INTERCEPT differs from LINEST

They are identical — LINEST simply returns more statistics.

Best Practices

  • Use INTERCEPT when you need only the regression intercept
  • Use SLOPE alongside INTERCEPT for manual predictions
  • Use TREND for multi-value forecasting
  • Use LINEST for full regression diagnostics
  • Remove outliers before modeling
  • Plot your data to confirm linearity
  • Use named ranges for cleaner formulas
INTERCEPT gives you the baseline of your trend — the point where your regression line crosses the Y-axis. It’s essential for understanding the starting level of any linear model.