The R-squared value (R²) is a key Six Sigma tool used to assess the goodness-of-fit of a regression model. It represents the proportion of variance in the dependent variable that is explained by the independent variables in the model. An R² value ranges from 0 to 1, with higher values indicating a better fit. By evaluating the R² value, organizations can determine how well the model captures the underlying data patterns. This helps in making data-driven decisions, optimizing processes, and improving quality, ensuring that the model reliably predicts outcomes and supports Six Sigma goals of efficiency and effectiveness.
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