SSE
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Lack-of-fit sum of squares and Pure-error sum of squaresStats/Inferential 2020. 2. 4. 12:17
1. Overview In statistics, a sum of squares due to lack of fit, or more tersely a lack-of-fit sum of squares, is one of the components of a partition of the sum of squares of residuals in an analysis of variance, used in the numerator in an F-test of the null hypothesis that says that a proposed model fits well. The other component is the pure-error sum of squares. 2. Description 2.1 Intuition $..
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Simple Linear RegressionMLAI/Regression 2019. 10. 20. 18:20
1. Overview Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable. For example, a modeler might want to relate the weights of individuals to their heights using a linear regression model. 2. Description 2.1 Process Ge..