1. The first statement is: "Cramer's Rule can only be applied to systems with exactly as many equations as unknowns." This is TRUE. Cramer's Rule requires a square coefficient matrix, meaning the number of equations must equal the number of unknowns. 2. The second statement is: "A binding constraint is one that does not affect the optimal solution of a linear programming problem." This is FALSE. A binding constraint is one that affects the optimal solution; it holds as an equality at the optimum. 3. The third statement is: "In Cramer's Rule, each variable's solution is determined by replacing the respective column of the coefficient matrix with the constant vector." This is TRUE. This is the core step in applying Cramer's Rule. 4. The fourth statement is: "Cramer's Rule can be used for non-linear systems of equations." This is FALSE. Cramer's Rule applies only to linear systems. Summary: - Statement 1: True - Statement 2: False - Statement 3: True - Statement 4: False This completes the evaluation of the statements.