Use of highly correlated variables in LR is known to render the model unstable due to multicollinearity. In fact, there were strong positive correlations between TC and LDL-C, AST and ALT, and moderate positive correlations between SBP and DBP, Alb and Ca, Na and Cl, and moderate negative...
1. It is important to check for outliers since linear regression is sensitive to outlier effects. 2. The linear regression analysis requires all variables must have normal distribution 3. Linear regression assumes that there is little or no multicollinearity in the data.A. 1 and 2...