Decision Science | Chapter 1 | Part 1 | MBA MCQs | DS

Decision Science MCQs

  

 

1. Decision Science approach is
   1.   Multi-disciplinary
   2.   Scientific
   3.   Intuitive
   4.   All of the above
2. For analyzing a problem, decision-makers should study
   1.   Its qualitative aspects
   2.   Its quantitative aspects
   3.   Both a & b
   4.   Neither a nor b
3. Its quantitative aspects
   1.   Controllable
   2.   Uncontrollable
   3.   Parameters
   4.   None of the above
4. A model is
   1.   An essence of reality
   2.   An approximation
   3.   An idealization
   4.   All of the above
5. Managerial decisions are based on
   1.   All of the above
   2.   Results generated by formal models
   3.   The use of qualitative factors
   4.   An evaluation of quantitative data
6. The use of decision models
   1.   Is possible when the variables value is known
   2.   None of the above
   3.   Reduces the scope of judgement & intuition known with certainty in decision-making
   4.   Require the use of computer software
7. Every mathematical model
   
   1.   Must be deterministic
   2.   Represents data in numerical form
   3.   All of the above
   4.   Requires computer aid for its solution
8. A physical model is example of
   
   1.   An iconic model
   2.   An analogue model
   3.   A verbal model
   4.   A mathematical model
9. The quantitative approach to decision analysis is a
   1.   Logical approach
   2.   Rational approach
   3.   Scientific approach
   4.   All of the above
10. An optimization model
    1.   Provides the best decision
    2.   Helps in evaluating various alternatives
    3.   All of the above
    4.   Provides decision within its limited context
11. The qualitative approach to decision analysis relies on
    1.   Experience
    2.   Judgement
    3.   Intuition
    4.   All of the above
12. The mathematical model of an LP problem is important because
    1.   It helps in converting the verbal description & numerical data into mathematical expression
    2.   Decision-makers prefer to work with formal models
    3.   It captures the relevant relationship among decision factors
    4.   It enables the use of algebraic technique
13. Linear programming is a
    
    1.   Constrained optimization technique
    2.   Technique for economic allocation of limited resources
    3.   Technique for economic allocation of limited resources
    4.   All of the above
14. A constraint in an LP model restricts
    1.   Value of objective function
    2.   Value of a decision variable
    3.   Use of the available resources
    4.   All of the above
15. The distinguishing feature of an LP model is
    1.   It has single objective function & constraints
    2.   Relationship among all variables is linear
    3.   Value of decision variables is non-negative
    4.   All of the above
16. Constraints in an LP model represents
    1.   Limitations
    2.   Requirements
    3.   Balancing limitations & requirements
    4.   All of the above
17. Non-negativity condition is an important component of LP model because
    1.   Value of variables make sense & correspond to real-world problems
    2.   Variables value should remain under the control of the decision-maker
       b.
    3.   Variables are interrelated in terms of limited resources
    4.   None of the above
18. Before formulating a formal LP model, it is better to
    1.   Express each constrain in words
    2.   Express the objective function in words
    3.   Verbally identify decision variables
    4.   All of the above
19. Maximization of objective function in an LP model means
    
    1.   Value occurs at allowable set of decisions
    2.   Both a & b
    3.   Highest value is chosen among allowable decisions
    4.   Neither of above
20. Which of the following is not a characteristic of the LP model
    1.   Alternative courses of action
    2.   An objective function of maximization type
    3.   Limited amount of resources
    4.   Non-negativity condition on the value of decision variables