least squares regression

a type of regression analysis in which the researcher strives to develop a least-squared-errors solution or least squares solution to describe the relationship between an outcome or dependent variable and one or more predictors or independent variables. That is, one develops a model that is the best fit for the data because it yields the smallest squared differences between the actual observations and their values as predicted by the model. Also called least squares estimation; ordinary least squares (OLS) regression. See least squares criterion.

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Psychology term of the day

February 25th 2025

simple structure

in exploratory factor analysis, a set of criteria for determining the adequacy of a factor rotation solution. These criteria require that each factor show a pattern of high factor loadings on certain variables and near-zero loadings on others and that each variable load on only one factor. This minimizes the complexity of the factor solution, allows each variable to be most strongly identified with a specific factor, and increases interpretability.