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The Impact Of Process Auditing On Production And Profitability In Manufacturing Company
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4.2 Hypothesis Testing
Hypotheses were tested in this research work for the purpose of this research work, regression analysis was used to test the hypotheses.
4.2.1 Model summary (R2)
The (R2) is summary measure that tells us has the sample regression line fits the data. It is also known as goodness of fit. It tells us by what percentage the variation in the dependent variable is explained by the independent variable of the model. This shows the percentage of the total variation of the dependent variable that can be explained by the independent variable(s). It shows the extent to which the independent variable(s) influences the dependent variable. It is a measure of the goodness of fit of the model; the closer the R2 is to zero the worse the fit.
4.2.2 The T-Test (Coefficients)
The test is carried out to ascertain whether the individual variables are statistical significant or not. It is used to determine the statistical significance of the parameters in the model. They will be tested at 1%, 5% and 10% levels of significance. The rule of thumb states that t≥2 is statistically significant. Any value below this is insignificant. From the coefficients table shows the effects and impacts of independents variables on the dependent variable.
4.2.3 The F-Test (ANOVA)
This is used to test the overall statically significant of the variables. It is meant to test the overall significance of the entire model as regards the dependent variable. It checks the joint variance of the explanatory variables. The level of significance to be used is 5%. Hence, if the probability is ≤ 0.05, the explanatory variables’ parameter estimates will be jointly statistically significant.
Hypothesis
H0: process auditing has no impact on production and profitability in manufacturing companies
H1: process auditing has impact on production and profitability in manufacturing companies
The correlation between Existence and the existence of an internal audit function and the profit levels is 0.85 which is 85%, meaning that they are linearly correlated, while the R2 is 0.57 meaning that 77% of the dependent variable could be explained by the independent variables.
The regression and residual equal to the sum of square and the ANOVA table shows that the F-cal. is 9.160 at 0.003 level of significant?
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