the ANOVA technique generalised them across the scope of study. The analysis was factorial because the researcher conducted experiments at all level of combinations of all the factors sampled. The efficiency of the experiments increased after the completion of every factor. The 3-way ANOVA tests posed one problem  the interactions of the variables could have created a false positive accidentally. However

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the ANOVA technique generalised them across the scope of study. The analysis was factorial because the researcher conducted experiments at all level of combinations of all the factors sampled. The efficiency of the experiments increased after the completion of every factor. The 3-way ANOVA tests posed one problem  the interactions of the variables could have created a false positive accidentally. However

while R2 0.124. The table below shows the products of the regression analysis

Model Summary.

Model R R Square Adjusted R Square Std. Error of the Estimate
1 .346(a) .124 .111 .63883

ANOVA (b).

Model Sum of Squares df Mean Square F Sig.
1 Regression 5.199 1 5.199 12.819 .001(a)
Residual 38.299 94 .403
Total 43.498 95

Coefficient (a).

Model Unstandardised Coefficients Standardised Coefficients T Sig.
B Std. Error Beta B Std. Error
1 (Constant) 2.358 .367 6.416 .000
X7PMM .310 .084 .344 3.580 .001

This paper used ANOVA tests to analyse the hypotheses proposed in the study. Since the study included multiple variances

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