- Get correlations
- Scatterplot of independent vs. dependent variable
- Density plot of variable distributions; check for normal distribution to use linear regression
- (Optional) Box plot to visualize outliers
- Build linear model
- Evaluate linear model: t-stat, p-value, goodness of fit with f-stat & standard error, adjusted r^2, AIC, BIC
- Rebuild linear model with training & test sets; measure accuracy via correlation of actual vs predicted values
- K-fold cross validation: cross-validate the linear model with k-folds; analyze
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Recipes for common linear regression operations: model comparisons, heteroskedasticity, collinearity, goodness of fit
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