Perform linear regression with a single predictor variable.
Estimate the standard error of regression coefficients.
Evaluate the goodness of fit of a regression.
Perform linear regression with multiple predictor variables.
Evaluate the relative importance of variables in a multiple linear regression.
Include interaction effects in a multiple linear regression.
Perform linear regression with qualitative predictor variables.
Model non-linear relationships using polynomial regression.
Identify non-linearity in a data set.
Compare and contrast linear regression with KNN regression.
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# 3. Linear Regression## Learning Objectives- Perform linear regression with a **single predictor variable.**- Estimate the **standard error** of regression coefficients.- Evaluate the **goodness of fit** of a regression.- Perform linear regression with **multiple predictor variables.**- Evaluate the **relative importance of variables** in a multiple linear regression.- Include **interaction effects** in a multiple linear regression.- Perform linear regression with **qualitative predictor variables.**- Model **non-linear relationships** using polynomial regression.- Identify **non-linearity** in a data set.- Compare and contrast linear regression with **KNN regression.**