“…Using a variety of diagnostic measures, including model fit, R2, change statistics, descriptions, parts and partial correlation, collinear diagnosis, Durbin-Watson, and Case-wise diagnostics, the researchers used multiple regression analysis in both Excel and SPSS for correlation and multi-regression computations (Binnie et al, 2021). As shown in Table 2, the regression coefficients and model fit, as well as the multiple R value (0.55), R square (0.30), and modified R square (0.22), were important elements in multiple regression analysis.…”