a. Dependent Variable: Organizational Performance
b. Predictors: (Constant), System Change, State of working conditions, Process Change & Business Change
The analysis of variance table (Anova table above) showed regression sum of square value of (175.631) which is higher than the residual sum of square value of (14.850). This implies that the model accounted for most of the variations in the dependent variable. More so, the F calculated value of (606.114) is greater than the tabulated value of (1.96) indicating a significant relationship. In addition, the significant value of P (0.000) is smaller than (0.05) which means that the independent variable (Change management implementation) is positively associated with the dependent variable (Organizational performance). Hence, we posited that there is significant relationship between change management implementation and Organizational performance at 5% level.

a. Dependent Variable: Organizational Performance
Based on the adjusted R square explained above, the four independent variables explain 92.1% of the variance of depended variable “Organizational performanceâ€. Using non- standardized weight of regression, multiple regression of equation can be presented as below:
Ŷ = β0 + β1x1+ β2x2 + β3x3 + β4x4 +εi
Ŷ = dependent variable “Organizational Performanceâ€
x1 = independent variable “System Changeâ€
x2 = independent variable “Change of working conditionsâ€
x3 = independent variable “Process Changeâ€
x4 = independent variable “Business Changeâ€
εi = stochastic error.
From the formula presented above, the Organizational performance is equal to the sum of non-standardized beta coefficients with the average of using the appropriate method and non standardized weight constant. From the multiple regression analysis results, the four independent variables are statistically meaningful for the model. They have regression coefficient positive which means with the raise of one of the independent variables factors will have even raise of the dependent variable in “Organizational performanceâ€. According to the results the statistical test for individual coefficient control the same result is taken (t1= 2.781 and p=0.006), (t2= 2.316 and p=0.022), (t3= 2.286 and p=0.023), (t4= 12.152 and p=0.000) individual coefficients showed that independent variables have a huge contribution for the model in order to improve Organizational performance. It is also possible to experience a slight reduction in Organization performance by 1.3% as the system change is poor, working condition is poorer, process and business change are faulty.