ANOVA calculator

Eta-squared and Partial Eta-squared calculator

Calculate Eta-squared (η²), Partial Eta-squared (ηₚ²), and Omega-squared (ω²) effect sizes for one-way and factorial ANOVA models.

Run this test live in StatLab npm i @statlab/core

When to use it

Use alongside ANOVA F-tests to report variance explained magnitude.

Required Inputs

  • Sum of Squares Between (SS_B)
  • Sum of Squares Error (SS_E)
  • Sum of Squares Total (SS_T)

Mathematical Formula

η² = SS_between / SS_total, ηₚ² = SS_between / (SS_between + SS_error), ω² = (SS_B - df_B*MS_E) / (SS_T + MS_E)

Reporting Cautions

  • Eta-squared tends to overestimate population effect size in small samples; use Omega-squared for unbiased estimation.
  • In factorial designs, Partial Eta-squared does not sum to 1.0 across factors.

Code Snippets (Python, R, TypeScript)

Python (SciPy / Statsmodels) 
def eta_squared(ss_b, ss_t):
    return ss_b / ss_t
def partial_eta_squared(ss_b, ss_e):
    return ss_b / (ss_b + ss_e)
R Language 
library(effectsize)
eta_squared(aov_model)
TypeScript (@statlab/core) 
import { etaSquared, partialEtaSquared } from '@statlab/core';
const eta2 = etaSquared(ssB, ssT);

Developer Use Cases & Production Integrations

  • Determining the proportion of variance explained by configuration parameters in benchmark runs.
  • Reporting standardized ANOVA effect sizes in VoxelAssurance release readiness audits.

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