F change: what it means and how to read it

In the report: F Change — The F test of R Square Change: whether the predictors added at this step explain more than chance. At the first step it equals the F of the model. Empty when the step entered no predictor (df1 = 0).

How to read it

Read its Sig. F Change; F itself goes into the report with df1 and df2 next to it: F(1, 7) = 15.39.

In plain words

A teacher guessed exam marks from hours of study, then added hours of sleep, and the guess became a little better. A fair question: is that gain real, or could it be luck? She looked at the F change and it came out 9.4 for her class. The bigger it is, the harder the gain is to put down to chance. A number near 1 would mean sleep adds no more than luck would. She also reads the chance column next to it, and it said the gain did not look like luck, so sleep stays in the guess.

How it is computed

F = (ΔR² / df1) / ((1 − R²ᵢ) / df2)

Example

The cell with F Change is selected in each report; point at a label to see its note.

  • — the sample data (50 rows) the examples use
  • — two steps: x1,x2, then x added =STATS_LINEAR(Data!A1:T51, "y", "x1,x2|x", 0)
  • — old syntax: regression steps, one-sample test against 15 =STATS_ANALYZE(Data!A1:T51, "linear(y|x1|x2) oneSample(x1|15)")

Where you see it

Get it in your sheet

One formula in a cell gives the whole report, F change included. ALS Stats is a free add-on for Google Sheets™.

Install ALS Stats from Google Workspace Marketplace (opens in a new tab)