For the following problems, we initially practice constructing simultaneous confidence intervals for parameters and predictions. Upon completion, you should be able to define all components of the confidence interval with proper notations and distinguish among its applications in various problems. Subsequently, we learn to define the matrix form for the Simple Linear Regression (SLR) model, which can be naturally extended to the Multiple Linear Regression (MLR) model with an expanded design matrix, parameter matrix, H matrix, and variance-covariance matrices