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Includes checking for multicollinearity (when variables are too similar), model adequacy, and using "dummy variables" for non-numerical data.
If you are searching for a high-quality academic EPUB on this topic, several reputable publishers offer comprehensive guides: Applied Linear Regression - Purdue Department of Statistics Regresion 1 Y 2 (Version Completa) epub
Finding the "best-fitting line" that minimizes prediction errors. Key Metrics: Interpretation of coefficients (slopes) and R2cap R squared Regresion 1 Y 2 (Version Completa) epub
values to determine how much variance is explained by the model. Regresion 1 Y 2 (Version Completa) epub
A "complete version" of a regression course or text generally covers the following progression:
Techniques like variable selection and validation to ensure the model works on new data. Where to Find it in EPUB