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Home/Regression Assumptions

Tag: Regression Assumptions

Multiple Linear Regression

Understanding the Difference Between R-squared and Adjusted R-squared in OLS Linear Regression Output

By Kanda Data / Date Jan 21.2024

R-squared (R²) and Adjusted R-squared (R² adjusted) are key metrics frequently used to assess the effectiveness of a linear regression model. The R-squared value provides information about the proportion of variability in the dependent variable explained by the independent variable in the linear regression equation.

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Multiple Linear Regression

Choosing the Right Variables in Linear Regression using the OLS Method

By Kanda Data / Date Oct 25.2023

Linear regression analysis is frequently employed by researchers to investigate the impact of independent variables on dependent variables. The Ordinary Least Squares (OLS) method is a popular choice among scholars for estimating parameters in linear regression models. The OLS technique aims to minimize the squared differences between observed and predicted values.

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