11. In a sensitivity analysis output when using Solver, which of the below is the range of optimality most commonly associated with? A) Only the actual number of each constrained resource used B) Only the optimal number of units to be produced C) The optimal number of units to be produced as well as the objective function coefficients, and the coefficients' respective allowable increases and decreases. D) The coefficients of the objective function, and the coefficients' respective allowable increases and decreases. 12. What is the most accurate definition of shadow price in the sensitivity reports generated by excel when using Solver? A) It is the price of the unsold items in the market B) It is the price that is already reduced of a certain product C) It is how much the cost should increase to make the product unworthy of being produced D) It is how much profit per unit that one additional unit a certain resource can get us 13. What is the statement that best characterises the range of feasibility? A) It shows only the final values of constraints and the allowable change of each constraint B) It shows the final values of constraints, the maximum/minimum values of the constraints, the allowable change, and the effect as a result of changes in the maximum/minimum values of the constraints. It is impossible to tell if a constraint is binding or non-binding just from the range of feasibility C) It shows the final values of constraints, the maximum (or minimum) values of the constraints, and the allowable change. It is possible to tell if a constraint is binding or non-binding from the range of feasibility D) It is irrelevant to the sensitivity data generated by excel 14. Why do we use different methods when modelling relationships between variables instead of using linear regression on every data type? A) Linear regression is only useful in non-financial cases B) Linear regression is only applicable when the relationship between variables is linear C) Linear regression is limited by slope and intercept and always comes with very high uncertainty D) Linear regression is providing an estimate for a value in future while other forecasting methods provide absolutely accurate values