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Home/Data Analysis in R

Category: Data Analysis in R

Data Analysis in R

How to Analyze Multicollinearity in Linear Regression and its Interpretation in R (Part 2)

By Kanda Data / Date Apr 17.2023

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.

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Data Analysis in R

How to Analyze Multiple Linear Regression and Interpretation in R (Part 1)

By Kanda Data / Date Apr 11.2023

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.

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