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Regression Analysis and Multicollinearity by Kevin Candra is a document available to read on EtoBox.

This document reports the results of a linear regression model with the natural log of y (lny) as the dependent variable and the natural log of x2, x3, and x4 (lnx2, lnx3, lnx4) as well as variables x5 and x6 as independent variables. The regression results show that the model has a high R-squared of 0.99 and all independent variables are statistically significant predictors of lny. Additional tests show no evidence of heteroskedasticity and high variance inflation factors, indicating potential issues with

Author

Kevin Candra

Language

EN