![one way anova examples one way anova examples](https://i.pinimg.com/originals/2c/f0/7c/2cf07c68a0ad9c94766f471f81689b82.jpg)
Our plants seem to be independent observations: each has a different id value (first variable).
#One way anova examples how to
So how to check if we meet these assumptions? And what to do if we violate them? The simple flowchart below guides us through. In this case, Levene's test can be used to see if homogeneity is met. Homogeneity is only needed for (sharply) unequal sample sizes. homogeneity: the variance of the dependent variable must be equal in each subpopulation.Normality is not needed for reasonable sample sizes, say each n ≥ 25. normality: the dependent variable is normally distributed in the population.Precisely, the assumption is “independent and identically distributed variables” but a thorough explanation is way beyond the scope of this tutorial.
![one way anova examples one way anova examples](https://www.researchgate.net/publication/275544647/figure/tbl1/AS:668940967608332@1536499363392/One-way-ANOVA-results-of-the-sample-data-regarding-familys-total-income-factor.png)
![one way anova examples one way anova examples](https://statistics.laerd.com/statistical-guides/img/one-way-anova-2.png)