A study over the Formulation of the Parameters 5 or Less Independent Variables of Multiple Linear Regression
Mehmet Korkmaz
Abstract
Open-access reader
Mehmet Korkmaz
Abstract
Open-access reader
As is known, finding the parameters of multiple linear regression is an important case. Of course, these parameters can be easily found with the help of the computer. In this study, in addition to the formula of the parameters of linear regression, the general formulas of the parameters of 5 and less independent variables of multiple linear regression are given with a certain order. The derivations of the formulas presented are given step by step. In addition to classical matrix form, these new formulas for estimation of the parameters of multiple linear regression could be proposed especially to the researchers not using computer program for calculating the complex operations. By using these formulas, the researcher can estimate easily the parameters of multiple linear regression without using a computer and so the researcher can compose easily the table of variance analysis to interpret the regression made. Since for 6 and more independent variables, the tables of the parameters of multiple linear regression are too long and they take up too much space, the general formulas of the parameters of 6 and more independent variables of multiple linear regression could not be given in this study.
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As is known, finding the parameters of multiple linear regression is an important case. Of course, these parameters can be easily found with the help of the computer. In this study, in addition to the formula of the parameters of linear regression, the general formulas of the parameters of 5 and less independent variables of multiple linear regression are given with a certain order. The derivations of the formulas presented are given step by step. In addition to classical matrix form, these new formulas for estimation of the parameters of multiple linear regression could be proposed especially to the researchers not using computer program for calculating the complex operations. By using these formulas, the researcher can estimate easily the parameters of multiple linear regression without using a computer and so the researcher can compose easily the table of variance analysis to interpret the regression made. Since for 6 and more independent variables, the tables of the parameters of multiple linear regression are too long and they take up too much space, the general formulas of the parameters of 6 and more independent variables of multiple linear regression could not be given in this study.
Key concepts: Linear predictor function, Proper linear model, Linear regression, Mathematics, Regression analysis, Regression diagnostic, Design matrix, Segmented regression