Tag: interpretation of multicollinearity test output
Non-Multicollinearity Test in Multiple Linear Regression
When analyzing data using linear regression using the Ordinary Least Square (OLS) method, it takes an understanding of the assumption test that must be passed. The non-multicollinearity test is necessary to get the best linear unbiased estimator. The multiple linear regression OLS method has been widely applied in various fields: economics, agribusiness, and socio-economic fields. The estimation of the output of this linear regression has many benefits. Various research problems can be solved with this analytical approach. When we choose to use regression analysis, we are trying to see the influence or impact of one or more variables on other variables. Therefore, many researchers, lecturers, students, and practitioners choose linear regression using the OLS method as a data analysis tool.