Tag: Breusch-Pagan Test
Differences in Assumptions of Normality, Heteroscedasticity, and Multicollinearity in Linear Regression Analysis
If you analyze research data using linear regression, it is crucial to understand the required assumptions. Understanding these assumption tests is essential to ensure consistent and unbiased analysis results.
How to Analyze Heteroskedasticity for Time Series Data in Multiple Linear Regression and Its Interpretation
The heteroskedasticity test is one of the assumption tests in the Ordinary Least Squares (OLS) linear regression method, aimed at ensuring that the residual variance remains constant. If the multiple linear regression equation being tested shows non-constant residual variance, this is referred to as heteroskedasticity.
How to Analyze Heteroskedasticity in Linear Regression Using R Studio
Heteroskedasticity testing is an assumption test in linear regression using the OLS method to ensure that the residual variance is constant. A constant residual variance is referred to as homoskedasticity.