📊 One-Way ANOVA Calculator
Paste your groups (one per line) to run a one-way ANOVA — with the F statistic, an SS/df/MS table, exact p-value and a significance verdict.
F statistic
16.667
df (between, within)
2, 12
p-value
0.0003
| Source | SS | df | MS |
|---|---|---|---|
| Between groups | 43.333 | 2 | 21.667 |
| Within groups | 15.6 | 12 | 1.3 |
| Total | 58.933 | 14 | — |
At least one group mean differs (significant at α = 0.05)
p = 0.0003 < 0.05, so you reject the null hypothesis that all 3 group means are equal. ANOVA doesn't say which groups differ — follow up with a post-hoc test (e.g. Tukey's HSD).
One-way ANOVA tests whether the means of three or more groups are all equal, by comparing the variance between group means to the variance within groups (the F ratio). p-values use the exact F-distribution. A significant result tells you the groups aren't all equal but not which ones — use a post-hoc test to locate the differences. It assumes roughly normal groups with similar variances. 🔒 In your browser.
How the one-way anova calculator works
One-way ANOVA tests whether the means of three or more groups are all equal. The tool computes the sum of squares between groups (how far the group means sit from the grand mean) and within groups (the spread inside each group), divides each by its degrees of freedom to get mean squares, and forms the F ratio (MS-between ÷ MS-within). The p-value comes from the exact F-distribution. Enter one group per line, values separated by commas or spaces.
ANOVA generalises the two-sample t-test to more than two groups without inflating the false-positive rate that running many separate t-tests would cause. A significant F only tells you that the groups are not all equal — not which ones differ; for that you run a post-hoc test such as Tukey's HSD. It assumes the groups are roughly normal with similar variances; for clearly non-normal data, a rank-based test like Kruskal-Wallis is safer. Everything runs locally in your browser.
Frequently asked questions
What does a one-way ANOVA test?
Whether the means of three or more independent groups are all equal. It compares the variation between the group means to the variation within the groups using an F ratio; a large F (small p-value) is evidence the means are not all equal.
Why not just run several t-tests?
Each t-test carries its own false-positive risk, and running many inflates the overall chance of a spurious "significant" result. ANOVA tests all groups at once at a single significance level, which controls that error rate.
What does the F statistic mean?
It's the ratio of between-group variance to within-group variance. If the group means are similar, F is near 1; the further apart the means are relative to the within-group spread, the larger F and the smaller the p-value.
A significant result — so which groups differ?
ANOVA doesn't say. A significant F means at least one group differs from another; to find out which, run a post-hoc test such as Tukey's HSD or pairwise comparisons with a correction.
Is my data uploaded?
No — the ANOVA is computed entirely in your browser and works offline, so your data never leaves your device.