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This was achieved by log-log regression, with the multiple regression tool of Stata 11.1 used to perform multiple linear regression of the logarithmic terms.
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This step provides an excellent opportunity to teach simple and multiple regression as tools for this purpose.
Design of experiments (DOE) coupled to multiple regression are powerful statistical tools to model the dependence of a physical, chemical or biological process to different intrinsic or extrinsic factors with a limited number of experiments [ 29].
The data analysis method helped us by correlation matrix tool and multiple regression.
The design experiments identified the main factors (SF, SP and W/B) and their interactions for all properties on the fresh and hardened state, showing that experimental design with multiple regression equations is an appropriate tool to be applied in this case.
The model was built up with the tool combination multiple regression (method best subsets) + ordinal multinomial distribution + the logit link function.
It employs multiple regression and correlation analyses as tools to assess the effects of two or more independent factors on the dependent variables [23].
A multiple regression model is used as statistical tool.
The data analysis included descriptive statistical tools and a multiple regression analytical technique.
In the present study, similar tools such as multiple regression, artificial neural networks, support vector machines and functional networks are trained to predict the deformability modulus of JGLF over time.
On establishing the desired performance measures and multiple regression models are developed to be used as predictive tools.
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