In order to test the hypothesis of this study uses a statistical software Eviews that have test the mathematical equation and will check the dependency of dependent variables over independent variables
. Regression analysis will be used to ascertain the 18 association among the defined variables and simultaneously correlation analysis have identified the significance relationship between variables.
In training set, the most correlated independent variables
[X.sub.1] and [X.sub.2] were added to a layer by creating a Sugeno fuzzy model (SFM) in both training and test sets, then intermediate output [U.sub.1] was obtained.
intention to leave and with the following independent variables
; training and development opportunities, recognition, peer relations.
In the case of multicollinearity among independent variables
, instead of directly applying the Least Squares method, the variables created by factor analysis that are uncorrelated with each other can be used (Draper and Smith, 1998; Ozkan, 2009).
In the future we shall further discuss the dynamic response to various perturbations (initial states, initial time, independent variables
, and dependent variables) and the second order sensitivity (showing the parameter sloppiness) at any time instant or around the steady state.
In this study all independent variables
are independent from each other.
Using the same methodology described above, but replacing the dependent variable, net outlays, with net cost of operations, once again the most suitable independent variable
is the POM (w/OCO) position.
The comparisons of the initial BCVAs between the cases with and without these five significant independent variables
are presented in Table 5.
Fortunately, machine learning, as a powerful technique for nonlinear fitting, is able to help us precisely acquire the values of CTP with the knowledge of some easy-measured independent variables
. With a sufficiently large database, a machine learning technique with appropriate algorithms can "learn" from the numerical correlations hidden in the dataset via a nonlinear fitting process and perform precise predictions.
In case of direct causal effect of leadership styles on the dependent variable, job satisfaction, the significant path coefficients for H6, H7, H8 and H9 affirmed that all four independent variables
have direct effect on the level of job satisfaction.
The purpose of multiple regression (a term used by Pearson, 1908) is to highlight the relation between a dependent variable (explained, endogenous or resultant variables) and a lot of independent variables
(explanatory, factor, exogenous, predictor ones).
Therefore, in 0.05level, the meaningful relationship exists between independent variable
(accuracy of profit forecast) and dependent variable (spent costs sticky of sold goods).