This case study analyzes the application of parametric and nonparametric statistical analyses with the multiple linear regression model in education and agricultural education research. The fields of education and agricultural education heavily rely on parametric analyses. We questioned the validity of the extensive use of such approaches after conducting a multiple linear regression analysis in an agricultural education project. Despite a large sample size, model assumptions were not met. A literature review spanning ten years of key field-specific journals revealed that nonparametric procedures were rarely used, with only 1.68% of 2,671 papers reporting such analyses. This scarcity highlighted the need to reconsider statistical approaches in these fields. Our case study examined how the Theory of Planned Behavior and Importance-Performance Variables influence behavioral intentions to engage in agricultural education programs and water conservation practices. An online survey was used to collect data from a nonprobability sample of 2,118 US residents having lawns with in-ground irrigation systems provided the data. Three assumptions of the multiple linear regression were not met, and the model did not generalize well in two partitions from the same dataset, leading us to employ quantile regression as a nonparametric alternative. Quantile regression fitted the data well and showed significant relationships. Our findings challenge the common misinterpretation of the Central Limit Theorem (CLT) in education and agricultural education research, underscoring the necessity for rigorous statistical criteria. This study demonstrates that relying solely on sample size and robustness to normality violations is inadequate and discusses more appropriate use of statistical criteria in deciding between parametric and nonparametric methods in linear regression. Readers will gain insights into the practical considerations of using quantile regression in fields where multiple linear regression may not suffice. The case study offers guidance on how to use the methodology, providing a framework that researchers can apply to their own projects. By following this case study, researchers will be better equipped to navigate similar challenges in their work, enhancing both the rigor and clarity of their research methodologies. [This content is provided in the format of an e-book.]