Which of the following is true about a linear regression model? \\ A regression model is "overt" when it is unable to accurately predict the training data \\ Extrapolation is when a regression model is applied to data not used for training \\ If an independent variable is associated with the dependent variable (significant slope), this could be due to a lurking variable or confounder. \\ Outliers in the y-direction more drastically affect a regression line than outliers in the xdirection ' In a linear regression model, the predictors must be close to normally distributed