Standardized coefficient β: what it means and how to read it
In the report: Beta — B in standard deviations: how many standard deviations Y changes for one standard deviation more of the predictor. The intercept has none.
How to read it
Beta puts predictors measured in different units on one scale: the larger |Beta|, the stronger the predictor within this model.
In plain words
A teacher found that one more hour of study went with 5 more points, and one more hour of sleep went with 2 more points. But hours of study and hours of sleep spread out in different ways, so she could not tell which one goes together with marks more strongly. She asked for Beta, which puts both on one common ruler. Study came out 0.6 and sleep 0.2. Now she can say that among these students, with both in the guess, study goes together with marks three times as strongly as sleep does.
How it is computed
Beta = B · sₓ / s_yExample
The cell with Beta is selected in each report; point at a label to see its note.
- — the sample data (50 rows) the examples use
- —
=STATS_LINEAR(Data!A1:T51, "y", "x1,x2", 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
STATS_LINEAR— Multiple linear regression (OLS) with hierarchical steps separated by | and interactions a*b.STATS_ANALYZE— Runs several analyses on one range and returns one report.
Related values
- Correlation coefficient r — The correlation coefficient: the strength and direction of the relation, from −1 to 1. Empty when a column has no spread or there are fewer than 2 common rows.
- Kendall’s tau-b — Kendall’s tau-b: pairs of rows ordered the same way in both columns minus pairs ordered the opposite way, over the pairs not tied, from −1 to 1. Empty when a column has no spread or there are fewer than 2 common rows.
- Partial correlation — The correlation of the two columns with the controls held constant: of what is left of both after the linear effect of the controls is removed. Empty when a control is constant or repeats another, or when there are fewer than k + 3 complete rows (k — the number of controls).
- Cohen's d — The effect size: the difference in standard deviations, so it does not depend on the units of the data. Empty when there is no spread.
- Phi — The strength of the relation, from the chi-square: for a 2 × 2 table with the sign of the relation (the sign depends on the order of the categories), for a larger table it equals the square root of χ² / N.
Get it in your sheet
One formula in a cell gives the whole report, Standardized coefficient β included. ALS Stats is a free add-on for Google Sheets™.
Install ALS Stats from Google Workspace Marketplace (opens in a new tab)