where Y is the predicted response; i is the linear coefficient; j is the
quadratic coefficient; b is the regression coefficient; k is the number
of factors studied and optimized in the experiment; and ˛ is the
random error.
The Minitab Release 14 Statistical Software was used for the
statistical design and data analysis to estimate the response of the
dependent variables and obtain the effects, coefficients, standard
deviation of coefficients and other statistical parameters of the
model. The optimum conditions were obtained graphically from
the contour plot and by solving the polynomial regression equation.
Goodness of fit was expressed by the coefficient of determination
R2. Statistical significance was analyzed through Analysis of Variance
(ANOVA), where the level of significance at a 5% probability
level was given as the P value with a 95% confidence level.