Please explain this regression using the Fama-french model

Regression Statistics Multiple R 0.918597599 R Square 0.8438215489 Adjusted R Square 0.8351449683 Standard Error 0.02003742694 Observations 58 ANOVA df SS MS F Significance F 97.25277574 0 Regression Residual Total 54 0.1171405244 0.03904684147 0.02168091783 0.0004014984783 0.1388214422 57 Standard Error Intercept Mkt-RF Coefficients 0.005132754506 0.9687703393 0.1506122472 -0.2783714412 0.002897139135 0.0638033857 0.1152262083 t Stat P-value Lower 95% Upper 95%ower 95.0 pper 95.0% 1.771663102 0.08209295083 -0.0006756597402 0.010941 -0.000679 0.010941 15.18368232 0 0.8408522528 1.096688.0.840852 1.096688 1.30710061 0.1967172781 -0.08040239129 0.381626: -0.080402 0.381626 -3.316909563 0.001632711525 -0.446630 83 -0.110112 -0.4466 -0.110112 SMB HML 0.08392494155 Regression Statistics Multiple R 0.918597599 R Square 0.8438215489 Adjusted R Square 0.8351449683 Standard Error 0.02003742694 Observations 58 ANOVA df SS MS F Significance F 97.25277574 0 Regression Residual Total 54 0.1171405244 0.03904684147 0.02168091783 0.0004014984783 0.1388214422 57 Standard Error Intercept Mkt-RF Coefficients 0.005132754506 0.9687703393 0.1506122472 -0.2783714412 0.002897139135 0.0638033857 0.1152262083 t Stat P-value Lower 95% Upper 95%ower 95.0 pper 95.0% 1.771663102 0.08209295083 -0.0006756597402 0.010941 -0.000679 0.010941 15.18368232 0 0.8408522528 1.096688.0.840852 1.096688 1.30710061 0.1967172781 -0.08040239129 0.381626: -0.080402 0.381626 -3.316909563 0.001632711525 -0.446630 83 -0.110112 -0.4466 -0.110112 SMB HML 0.08392494155