summarize: Regression statistics refer to a set of statistical methods used to estimate the relationships between independent and dependent variables. These methods help understand how the dependent variable changes when any one of the independent variables is varied (Woo, 2019). The coefficient of determination (R) represents the proportion (percentage) of variance in the dependent variable shared with the variance of the independent variable in regression statistics. It measures how well the regression statistics explain the variability of the dependent variable. R2 is calculated from (Pearson's r)2. Where R2 = 0, the regression explains none of the variability of the response and if R2 = 1, the regression statistics explain all the variability of the response data around its mean (Woo, 2019). A higher value indicates a better fit of the regression statistic observed data; the greater proportion of the variance in the dependent variable is explained by the independent variables (Salkind & Frey, 2022). Regression and the coefficient of determination are fundamental tools in statistical analysis for modelling and analyzing the relationships between variables, making predictions, and drawing insights from data