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Gnumeric · Statistical analysis · Intermediate

Fit a Linear Regression in Gnumeric

Run Gnumeric regression analysis on X and Y data, read the intercept and slope, and avoid common input-range mistakes.

Official documentation reviewed; native application verification pending · Updated 10 October 2026 · Editorial standards

A linear regression models a response Y as a function of one or more predictor variables X. In Gnumeric, the Regression analysis tool can produce a regression summary, including estimated coefficients and other statistics.

Practice with an exactly linear dataset

Import paired variables (CSV). For this exercise, use X as the predictor and Y as the outcome. The sample is deliberately constructed from the equation:

Y = 1 + 2 × X

Therefore the expected intercept is 1, expected slope is 2, and R-squared is 1 (a perfect demonstration fit). Real measurement data almost never fit so perfectly.

Use Gnumeric’s regression tool

  1. Identify the X and Y columns after importing the CSV. If the sample starts at A1, X is A2:A9 and Y is B2:B9.
  2. Open Regression within Gnumeric’s statistical-analysis tools.
  3. Specify the predictor range in X Variables and the outcome range in Y Variable.
  4. If you include row 1 in both input ranges, enable Labels. Otherwise exclude both headings consistently.
  5. Keep Force Intercept To Be Zero off: our known equation has an intercept of 1.
  6. Output results to a separate sheet and locate the slope and intercept estimates.

Check the result

A fitted value for X=6 should be 1 + 2×6 = 13. You can also compare against the SLOPE and INTERCEPT function guides.

Troubleshooting

  • Wrong variable roles: swapping X and Y produces a different regression equation, even if the correlation stays the same.
  • Forced zero intercept: that changes the model; do not enable it merely to make results appear simpler.
  • Misaligned observations: each Y must correspond to the X from the same row.
  • No residual variation: this perfect sample is useful for learning coefficients, but it is not appropriate for interpreting p-values or standard errors as in a real study.

Verification note: Coefficients were checked independently from the dataset. Menu workflow is documentation-checked, not native-app-tested.

Official source: Application handbook or manual. This guide is an editorial draft prepared for staging; exact menus and outputs must be checked in the target software/version before public release.