# Table 46 anova anova a model sum of squares df mean

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Table 4.6: ANOVA ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 394.439 4 98.610 8.003 .000 b Residual 1441.668 117 12.322 Total 1836.107 121 a. Dependent Variable: Project implementation b. Predictors: (Constant), Budget allocation, Project mission, Project resources, Management Multiple Regression: Table 4.7: Multiple Regression Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3.104 2.640 2.176 .002 Project mission .449 .123 .322 3.644 .000 Project resources .110 .124 .076 2.888 .003 Management .292 .113 .251 2.590 .001 Budget allocation .547 .122 .435 4.475 .000 a. Dependent Variable: Project implementation The regression equation was: Y = 3.104 + 0.449 X 1 + 0.110 X 2 + 0.292 X 3 + 0.547 X 4 Where; Y = the dependent variable (Project Implementation) X 1 = Project Mission X 2 = Project Resources X 3 = Management X 4 = Budget Allocation The regression equation above has established that taking all factors into account (project implementation as a result of project mission, project resources, management and budget allocation) constant at zero project implementation was 3.104. The findings presented also shows that taking all other independent variables at zero, a unit increase in project mission will lead to a 0.449 increase in the scores of project implementation; a unit increase in project resources will lead to a 0.110 increase in project implementation; a unit increase in management will lead to a 0.292 increase in the scores of project implementation; a unit increase in budget allocation will lead to a 0.547 increase in the score of governance. This therefore implies that all the four variables have a positive relationship with budget allocation contributing most to the dependent variable.
ISSN 2394-9694 International Journal of Novel Research in Humanity and Social Sciences Vol. 5, Issue 4, pp: (53-69), Month: July - August 2018, Available at: Page | 65 Novelty Journals From the table we can see that the predictor variables of project implementation as a result of project mission, project resources, management and budget allocation got variable coefficients statistically significant since their p-values are less than the common alpha level of 0.05. Table 4.8: Hypotheses Testing Research Hypothesis β t Sig. Comments HO 1 : Project mission has no significant influence on water project implementation in Coast Water Services Board .322 3.644 .000 Reject H 0 1 HO 2 : Project resources has no significant influence on water project implementation in Coast Water Services Board .076 2.888 .003 Reject H 0 2 HO 3 : Management has no significant influence on water project implementation in Coast Water Services Board .251 2.590 .001 Reject H 0 3 HO 4 : Budget Allocation has no significant influence on water project implementation in Coast Water Services Board .435 4.475 .000 Reject H 0 4 5. SUMMARY OF THE FINDINGS, CONCLUSION AND RECOMMENDATION Summary of the findings: From the research findings, project mission had an influence on implementation of water projects in Coast Water Services Board. Majority of the respondents found project planning, project objectives and project goals as key indicators that help administer project implementation in Coast Water Services Board. The findings revealed that project planning, project

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