Bartlett's Test
Android app by UKM APPS. Education · UKM APPS
- Store rating
- Unknown
- Store rating count
- Unknown
- Download price
- Free to download
- In-app purchases
- Not listed in captured metadata
- Version
- 1.6
- Listing last refreshed
- 2026-09-16
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Store description excerpt
Bartlett's Test — check the equal-variance assumption behind ANOVA and the pooled t-test, right on your phone. Many classic tests assume every group has the same spread (variance). Bartlett's test is the normal-theory way to check it: do your groups really share one common variance, or is one of them far more erratic than the rest? Enter your data and get a clear verdict in seconds. WHAT YOU CAN DO • Enter 2 to 6 groups of values and run Bartlett's test instantly. • Read the verdict in plain language: variances look equal, or the assumption fails. • See each group's mean, variance and standard deviation in a clean table. • Get the full numbers: Bartlett's chi-square statistic, degrees of freedom, the p-value, the pooled variance, the Bartlett correction C and the max/min SD ratio. SEE IT, DON'T JUST READ IT • Per-group variance bars compared against the pooled variance line. • Spread bands that show each group on a shared axis. • The chi-square curve with the 5% rejection tail and your statistic marked on it. EXPLORE AND LEARN • Idea — why equal variances matter, with the pooled-variance formula and the statistic, rendered with offline KaTeX (no internet needed for the math). • Simulate — keep every group's mean identical and stretch just one group's spread. Type a value, tap the − / + steppers, or drag the slider, and watch the test light up on variance alone. • Cases — worked, real-world style examples: erratic filling machines, well-behaved labs, and one wildly variable group. THE MATH • Pooled variance: Sp² = Σ(nᵢ−1)·sᵢ² / (N−k) • Statistic: χ² = [(N−k)·ln Sp² − Σ(nᵢ−1)·ln sᵢ²] / C, with the Bartlett correction C • Degrees of freedom k−1, with the p-value from the chi-square distribution WHO IT'S FOR Students, teachers, researchers, QA and quality-control engineers, data analysts — anyone who needs to justify (or question) the equal-variance assumption before running ANOVA or a t-test. Tip: Bartlett's test assumes roughly normal data; Levene's test is the robust alternative for non-normal data. Clean, fast, and works offline. A small banner ad helps keep the app free.
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