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.
To address the research question and achieve the objective of the study, correlation and statistical linear regression analysis was done to predict the values of response variables (
dependent variables: physico-chemical characteristics of SPM) through explanatory variables (independent variable: physico-chemical characteristics of inert matter/material/waste) [30].
The slope intercept form of a linear equation (y=mx+b) is the means by which to do this, where y is the predicted value of the
dependent variable (net outlays), m is the slope of the line, x is the independent variable (POM w/OCO position), and b is the intercept of the line with the Y-axis.
Discriminant analysis is a multivariate technique which focuses on association between categorical
dependent variables and multiple independent variables.
Regression between the independent variables (quality of service) and the
dependent variable (behavior change) showed that there was a significant inverse correlation between these two variables.
The method of multiple regression is generalized through the theory of the "general linear model", in which there are more
dependent variables simultaneously, as well as variables that are not independent from a linear point of view.
(2012) use logarithm of GDP as the
dependent variable. Strictly speaking, they regress the change in the logarithm of GDP on the change in the logarithm of the resource measure, which is in effect the first differenced regression of logarithm of GDP on logarithm of the resource measure.
For example, a study would be considered to have neutral or mixed effects if a functional relationship were established between the independent and
dependent variables with positive effects for two of four participants in an ABAB study, but no effects or negative effects were observed for the remaining participants.
Fundamentals of Financial Management, 12/E, Financial Times Press Table 2: Regression analysis,
dependent variable: ROCA, n = 2493 Coefficient Std.
The independent variables have a 76% effect on the
dependent variable as shown by the R value of .76 which shows that up to 76% of the depend variable is caused by the independent variables.
The second way a lagged
dependent variable "can suppress the explanatory power of other independent variables" (Achen 2001, 1) is that the lagged variable controls for the factors that made the
dependent variable what it was in period t-1--the same factors that are impacting it in period t.