Σύγκριση μεθόδων

	Έλεγχος Bartlett για την Ομοιογένεια των Διακυμάνσεων	Δοκιμή Fligner-Killeen για Ομοιογένεια Διασπορών	Μονόδρομη Ανάλυση Διακύμανσης
Πεδίο	Στατιστική	Στατιστική	Στατιστική
Οικογένεια	Hypothesis test	Regression model	Hypothesis test
Έτος προέλευσης	1937	1976	1925
Δημιουργός	Maurice Stevenson Bartlett	Michael A. Fligner & Timothy J. Killeen	Ronald A. Fisher
Τύπος	Parametric variance homogeneity test	Rank-based test for homogeneity of variances	Parametric mean comparison
Θεμελιώδης πηγή	Bartlett, M. S. (1937). Properties of sufficiency and statistical tests. Proceedings of the Royal Society of London. Series A, 160(901), 268–282.	Fligner, M. A., & Killeen, T. J. (1976). Distribution-Free Two-Sample Tests for Scale. Journal of the American Statistical Association, 71(353), 210-213.	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.
Εναλλακτικές ονομασίες	Bartlett's Chi-Square Test, Test for Equality of Variances, Bartlett's Homogeneity Test, Varyans Homojenliği Testi	Fligner-Killeen test of variance homogeneity, rank-based variance homogeneity test, Fligner-Killeen Varyans Homojenliği Testi	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Συναφείς	2	5	4
Σύνοψη	Bartlett's Test is a classical parametric procedure for testing whether two or more independent groups share a common population variance. Introduced by Maurice Stevenson Bartlett in 1937, it formalises the null hypothesis that all group variances are equal by constructing a chi-square statistic from the ratio of pooled to individual group variances. It is a standard pre-analysis step before applying ANOVA or other procedures whose validity depends on the homoscedasticity assumption.	The Fligner-Killeen test is a rank-based test that checks whether several independent groups share the same variance (scale). Introduced by Fligner and Killeen in 1976, it does not require the data to be normally distributed, making it a robust nonparametric alternative to the Levene and Bartlett tests.	One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925.