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Tag: multicollinearity test in R

Multicollinearity Test in R Studio for Multiple Linear Regression Using Time Series Data

By Kanda Data / Date Dec 23.2024 / Category Data Analysis in R

In time series data analyzed using multiple linear regression with the ordinary least squares (OLS) method, it is also necessary to test for multicollinearity. The multicollinearity test is one of the assumption tests to ensure the best linear unbiased estimator.

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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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