The one-way ANOVA test explained.

Why you should read this article: • To understand the methodology of the one-way ANOVA test as an example of an inferential statistical method • To understand the Kruskal-Wallis H test as an alternative when the assumptions needed for the one-way ANOVA test do not hold • To identify and assess the clinical significance of findings Background: Quantitative methods and statistical analysis are essential tools in nursing research, as they support researchers testing phenomena, illustrate their findings clearly and accurately, and provide explanation or generalisation of the phenomenon being investigated. The most popular inferential statistics test is the one-way analysis of variance (ANOVA), as it is the test designated for comparing the means of a study's target groups to identify if they are statistically different to the others. However, the nursing literature has identified that statistical tests are not being used correctly and findings are being reported incorrectly. Aim: To present and explain the one-way ANOVA. Discussion: The article presents the purpose of inferential statistics and explains one-way ANOVA. It uses relevant examples to examine the steps needed to successfully apply the one-way ANOVA. The authors also provide recommendations for other statistical tests and measurements in parallel to one-way ANOVA. Conclusion: Nurses need to develop their understanding and knowledge of statistical methods, to engage in research and evidence-based practice. Implications for practice: This article enhances the understanding and application of one-way ANOVAs by nursing students, novice researchers, nurses and those engaged in academic studies. Nurses, nursing students and nurse researchers need to familiarise themselves with statistical terminology and develop their understanding of statistical concepts, to support evidence-based, quality, safe care. [ABSTRACT FROM AUTHOR]