One-way ANOVA
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In statistics, one-way analysis of variance (abbreviated one-way ANOVA) is a technique used to compare means of two or more samples (using the F distribution). This technique can be used only for numerical data.
Assumptions
The results of a one-way ANOVA can be considered reliable as long as the following assumptions are met:
- Response variable must be normally distributed (or approximately normally distributed).
- Samples are independent.
- Variances of populations are equal.
ANOVA is a relatively robust procedure with respect to violations of the normality assumption (Kirk, 1995) If data are ordinal, a non-parametric alternative to this test should be used - Kruskal-Wallis one-way analysis of variance.
References
- R. E. Kirk (1995). "Experimental Design: Procedures For The Behavioral Sciences", Third Edition, Pacific Grove, CA, USA: Brooks/Cole.Template:Math-stub
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