MHA5017_RebeccaOjo_Assessment3

3 Regression Statistics Multiple R 0.336262892 R Square 0.113072733 Adjusted R Square 0.098372281 Standard Error 2482.428639 Observations 185 ANOVA df SS MS F Significance F Regression 3 142200787.6 47400262.5 7.69178615 7.25547E-05 Residual 181 1115403803 6162451.95 Total 184 1257604590 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 6652.176243 2096.817927 3.17251019 0.00177571 2514.825184 10789.5273 2514.825184 10789.5273 age 107.0358985 28.91090095 3.70226783 0.0002835 49.99015068 164.0816463 49.99015068 164.0816463 risk 153.5570698 66.68461014 2.30273626 0.02243122 21.97786172 285.1362779 21.97786172 285.1362779 satisfaction -9.194689858 6.358071506 -1.4461445 0.14986607 -21.74016342 3.350783708 -21.74016342 3.350783708 According to Xia (2020), variance analysis aids hospital researchers in determining the equality of three or more groups. This is demonstrated by the ANOVA value in the tables above. Accepting this regression model might be wise, for instance, if the value of F (significance) is smaller than alpha, or.05. Here, 7.25547E-05, the significance factor, is less than alpha. This number indicates a p-value of 0.0002835 and a beta coefficient of 107.04 for age. This demonstrates how cost and age relate to one another can have important consequences (Wang et al., 2019). A p-value of 0.14987 and a beta value of -9.19469 are displayed when viewing the satisfaction beta value. The association between the independent and outcome variables (cost) is negative, as indicated by the negative value, while the p-value is positive. The variable in this instance therefore has no significant link with, as indicated by a larger p-value than the alpha value.