Analysis of Variance (ANOVA) is designed to test differences in means between any two or more groups and only whether a difference exists (Holt, 2024). In the GCU Core Quantitative Designs document ex post facto design, comparative design, and any of the experimental designs could use ANOVA as a statistical test of the hypothesis (Grand Canyon University, 2020). Each of these designs compares two or more groups. However, whether to use ANOVA or not will always depend on the alignment with the purpose of the study. In the example above, the components presented do offer good alignment. The problem statement, research questions, and hypotheses all focus on the extent GPA and test scores differ by grade. The independent variable is the grade in high school. The dependent variables are the GPA and the standardized test scores. I believe ANOVA would be an adequate means to address the research question. The design appears to seek a comparison of scores (mean) by grade (four groups) and does not seek to predict or look for a strength or direction in the relationship (Grand Canyon University, 2020). Grand Canyon University. (2020). Quantitative core designs. DC Network. https://dc.gcu.edu/dissertation/dissertation-templates/6_core_designs/quantitative_gcu_core_designs_08_10_20docx Holt, M. P. (2024). Analysis of variance