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Ordinary least-squares (OLS) models assume that the analysis is fitting a model of a relationship between one or more explanatory variables and a continuous or at least interval outcome variable that minimizes the sum of square errors, where an error is the difference between the actual and the predicted value of the outcome variable. The most common analytical method that utilizes OLS models is linear regression (with a single or multiple predictor variables).
Description
Ordinary least-squares (OLS) models assume that the analyst is fitting a model of a relationship between one or more explanatory variables and a continuous or at least interval outcome variable that minimizes the sum of square errors, where an error is the difference between the actual and the predicted value of the outcome variable. The most common analytical method that utilizes OLS models is linear regression (with a single or multiple...
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Zdaniuk, B. (2023). Ordinary Least-Squares (OLS) Model. In: Maggino, F. (eds) Encyclopedia of Quality of Life and Well-Being Research. Springer, Cham. https://doi.org/10.1007/978-3-031-17299-1_2008
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DOI: https://doi.org/10.1007/978-3-031-17299-1_2008
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