Assess learners' ability to apply ordinary least squares (OLS) linear regression to real business data by selecting predictors, estimating and interpreting coefficients, checking OLS assumptions (linearity, independence, homoscedasticity, normality), performing residual diagnostics, evaluating goodness-of-fit, and producing short-term forecasts with prediction intervals; include tasks on model validation (train/test split or cross-validation) and justification of modeling choices using provided datasets.