STEYX Function (LibreOffice Calc)
The STEYX function in LibreOffice Calc returns the standard error of the predicted Y-values in a linear regression. This guide explains syntax, interpretation, examples, 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.
What the STEYX Function Does
- Calculates the standard error of the estimate
- Measures the typical vertical distance between data points and the regression line
- Works with numeric X/Y pairs
- Useful for regression diagnostics and model evaluation
- Works across sheets
A smaller STEYX means a better‑fitting model.
Syntax
STEYX(known_y; known_x)
Where:
known_y— dependent variable (Y values)known_x— independent variable (X values)
Interpretation of STEYX
| STEYX Value | Meaning |
|---|---|
| Near 0 | Excellent fit — points lie close to the regression line |
| Small | Good fit |
| Large | Poor fit — high scatter around the line |
STEYX is measured in the same units as Y.
Basic Examples
Standard error of regression
=STEYX(B1:B10; A1:A10)
Across sheets
=STEYX(Sheet1.B1:B50; Sheet2.A1:A50)
Using named ranges
=STEYX(Sales; MarketingSpend)
With dates as X-values
=STEYX(B1:B100; A1:A100)
(Calc converts dates to serial numbers.)
Advanced Examples
STEYX ignoring errors
=STEYX(IF(ISNUMBER(B1:B100); B1:B100); IF(ISNUMBER(A1:A100); A1:A100))
(Confirm with Ctrl+Shift+Enter in older Calc.)
STEYX using filtered (visible) data only
Use SUBTOTAL helper column to filter X/Y before passing to STEYX.
STEYX after removing outliers
=STEYX(FILTER(B1:B100; B1:B100<1000); FILTER(A1:A100; B1:B100<1000))
STEYX for log-transformed regression
=STEYX(LN(B1:B10); LN(A1:A10))
STEYX for exponential regression (manual)
Exponential model:
y = b * m^x
Linearized:
=STEYX(LN(Y1:Y20); X1:X20)
STEYX from LINEST (full regression)
=INDEX(LINEST(B1:B10; A1:A10; TRUE; TRUE); 3; 2)
How STEYX Calculates Standard Error of Estimate
The formula is:
[ SE = \sqrt{\frac{\sum (y_i - \hat{y}_i)^2}{n - 2}} ]
Where:
- ( y_i ) = actual Y
- ( \hat{y}_i ) = predicted Y from regression
- ( n ) = number of data points
This is the standard deviation of the residuals.
Common Errors and Fixes
Err:502 — Invalid argument
Occurs when:
- X and Y ranges have different sizes
- One or both arrays contain no numeric values
- Fewer than 3 data points (n - 2 must be > 0)
Err:504 — Parameter error
Occurs when:
- Semicolons are incorrect
- Range references malformed
STEYX returns unexpectedly large value
Possible causes:
- Poor linear fit
- High scatter in data
- Outliers
- Non-linear relationship
STEYX differs from LINEST
They are identical — LINEST simply returns more statistics.
Best Practices
- Use STEYX to evaluate regression accuracy
- Use RSQ to measure explained variance
- Use LINEST for full diagnostics (F-statistic, df, etc.)
- Remove outliers before modeling
- Plot residuals to check for non-linearity
- Use named ranges for cleaner formulas