Category: Data Analysis in R
How to Analyze Multicollinearity in Linear Regression and its Interpretation in R (Part 2)
Non-multicollinearity is one of the assumptions required in the ordinary least square (OLS) method of linear regression analysis. Non-multicollinearity assumption implies that there is no strong correlation among the independent variables in the equation.
How to Analyze Multiple Linear Regression and Interpretation in R (Part 1)
Multiple linear regression analysis has been widely used by researchers to analyze the influence of independent variables on dependent variables. There are many tools that researchers can use to analyze multiple linear regression.