The Analysis of Variance (ANOVA) test has long been an essential tool for researchers conducting studies on multiple experimental groups with or without one or more control groups. This article encapsulates the fundamentals of ANOVA for an intended benefit of the reader of scientific literature who does not possess expertise in statistics. The emphasis is on conceptually-based perspectives regarding the use and interpretation of ANOVA results, with minimal coverage of the mathematical foundations. Data entry, checking basic parametric assumptions of ANOVA, descriptive statistics of the data by treatment groups, fitting ANOVA model, statistical significance of the test based on p-value, and post-hoc analysis are all explored using R-software.