USING ANALYSIS OF VARIANCE AND TUKEY'S TEST TO COMPARE FOUR BRANDS OF INDUSTRIAL PAINT

Abstract

Objective: The aim of this paper is to show the application of Analysis of Variance and Tukey's Test to compare four brands of paint used in a company's production. Theoretical framework: Analysis of Variance, or ANOVA, is a statistical method used to determine whether there are significant differences between the means of three or more independent groups. This technique was developed by the British statistician and geneticist Ronald Fisher at the beginning of the 20th century (Bosco v & Bispo, 2010). Method: Data was taken from a company in the South of Rio de Janeiro and a case study was carried out using Analysis of Variance and Tukey's test. Final Considerations: This result indicates that the hardness of the paint mixtures differs significantly. Some of the group averages are known to be different. Tukey's comparison results were used to formally test whether the difference between a pair of groups is statistically significant. It was found that Paint 4 has a higher hardness than the others. Implications of the research: The use cases of Analysis of Variance and Tukey's Test are multiplying in the scientific literature and are proving to be highly effective for processing data in a wide variety of areas. Originality/value: Despite being well-known statistical tools, Analysis of Variance and Tukey's Tests are only valid in cases where there are more than two types of samples in which the statistical assumptions have been confirmed.