UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION B Sc. Mathematics (2011 Admission Onwards) II SEMESTER Complementary Course

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1 UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION B Sc. Mathematics (2011 Admission Onwards) II SEMESTER Complementary Course MATHEMATICAL ECONOMICS QUESTION BANK 1. Which of the following is a measure of inequality in variables a. Lorenz curve b. Coefficient of variation c. Pareto distribution d. all the above 2. Which of the following is a graphical method of measuring inequality a. Lorenz curve b. Mean deviation c. Lognormal distribution d. None of these 3. is a measure of inequality in variables. a. Binomial distribution b. Poisson distribution c. Pareto distribution d. None of these 4. An increase in a personal command over resources during a given period of time is called a. Profit b. Income c. Consumption d. None of these 5. While drawing Lorenz curve, cumulative percentage of income is taken along the a. X-axis b. Y-axis c. XY plane d. None of these 6. The line joining (0,0) to (100,100) in a Lorenz Curve is called a. Line of equal distribution b. sloping line c. Line of perfect inequality d. None of these 7. The farther the Lorenz curve from the line of equal distribution, the... inequality in income. a. Lesser b. Poorer c. greater d. moderate 8. The divergence between Lorenz curve and line of perfect equality can be measured by a. Gini coefficient b. Correlation coefficient c. Coefficient of variation d. None of these 9. The range of the Gini coefficient is a. -1 to +1 b. - to + c. 0 to 1 d -1 to 0 MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 1

2 10. The area between the line of perfect equality and the Lorenz curve divided by the area of the triangle below the line is the a. Gini index b. Pareto index c. Paasche's index d. None of these 11. Lorenz curve is named after a. R.A. Fisher b. Amarthya Sen c. Max O' Lorenz d. Pareto Wilfred 12. Lorenz curve is an indicator for the distribution of two factors a. being equal b. being unequal c. both a and b d. neither a nor b 13. In LPP, the simplex method was developed by a. Koopman b. G.B. Dantzig c. Leonteif d. None of these 14. In LPP the transportation problem was contributed by a. Leonteif b. Koop man c. G.B. Dantzig d. None 15. In LPP, the diet problem was introduced by a. Stigler b. G.B. Dantzig c. Koopman d. Non 16. With regard to the requirements of LPP, the limited resources are usually expressed as a. objective function b. Decision variables c. constraints d. None 17. Which of the following is an assumption of LP. a. certainty b. Divisibility c. Additivity d. All the above 18. is a primary requirement of a LP a. Continuity b. Linearity c. Additivity d. None 19. Which of the following is required to formulate a LPP a. objective function b. decision variables c. constraints d. All the above 20. Any non negative value of (x 1, x 2 ) is a of the LPP if it satisfies all the constraints. a. feasible region b. critical c. feasible solution d. None 21. The collection of all feasible solution is called a. feasible region b. critical region c. optimal solution d. None MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 2

3 22. Any non negative value of (x 1, x 2 ) is a feasible solution of the LPP if it satisfies all the a. non negativity conditions b. constraints c. objective function d. None 23. A linear inequality in two variables is known as a a. half plane b. Closed half plane c. XY plane d. None 24. The optimal solution any LPP corresponds to one of the of the feasible region. a. turning points b. corner points c. maximum point d. None 25. LP is a quantitative technique of decision making using constraints a. inequality b. equality c. both and b d. None 26. In which of the following fields, LP can be used as a technique of decision making. a. production b. marketing c. financial d. None 27. In LPP we deal with objectives a. many b. only one c. two d. None 28. One of the limitations of LPP is to satisfy the assumption of of objective function and constraints. a. certainty b. continuity c. linearity d. None 29. Extreme points w.r.t & LPP are also known as a. vertices b. corner points c. both a & b d. None 30. LPP where the objective function coincides with one of half planes generated by a constraint will possess a. multiple solution b. unique solution 31. If no feasible solution of the problem exists, then that LPP is said to be a. unbounded b. bounded c. infeasible d. feasible 32. An unbounded solution of a LPP is a solution whose objective function is a. finite b. unique c. infinite d. None 33. The effect of changes in the coefficient in the optimum value of the objective function can be studied through a technique called MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 3

4 a. simplex method b. sentitivity analysis c. assignment problem d. None of these 34. Every linear programming problem has a associated with it a. dual problem b. transportation problem c. assignment problem d. None of these 35. Dual of the dual is called a. simplex b. objective function c. primal d. None 36. The variables of the dual problem are known as a. dual variables b. shadow prices 37. A system has 3 equations with 3 variables. If it is solvable, such a solution is called a. optimal solution b. basic solution c. multiple solution d. None 38. In a simplex method, the variables which are equated to zero are called a. basic variables b. nonbasic variables c. random variables d. None 39. A basic solution in a LPP is a if it is feasible. a. basic feasic solution b. Non basic feasible solution 40. A system with m equations and n variables has at most basic solutions a. n m b. m n c. ccm d. None of these 41. A basic solution with m equations and n variables has variables equal to zero a. n m b. m n c. ncm d. None of these 42. A basic feasible solution is a basic solution whose variables are a. feasible b. negative b. non negative d. None 43. The maximum number of basic feasible solutions in a system with m equations and n variables is a. ncm b. n m c. m-n d. None 44. The objective function of a LPP is optimised at a solution a. basic b. basic feasible c. non basic d. None MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 4

5 45. Variables can convert greater than or equal to type constraints into equations. a. Surplus variables b. Slack variables c. basic variables d. None 46. If in the course of simplex computation Zj-Cj<0 but y ij < 0 for all i, then the problem has a. one finite solution b. no finite solution 47. The number of in the primal problem is equal to the number of dual variables a. Objective function b. non negativity condition c. constraints d. None of these 48. If the primal problem is a maximisation problem, then the dual problem is a problem a. minimisation b. transportation c. assignment d. none 49. An is a non negative variable introduced to introduced to facilitate the computation of an initial basic feasible solution. a. optimal variable b. artificial variable 50. The problem is the original linear programming problem a. dual b. Transportation c. primal d. None 51. The method of solving LPP with greater than or equal to type constraints is: a. Two phase method b. M method 52. is a quantitative measure of satisfaction a person gets at the end of the game: a. pay off b. strategy c. game theory d. none 53. Two person matrix game is always a game a. positive sum b. negative sum c. zero sum d. none 54. The set of all possible pay offs displayed in a table is called a. zero matrix b. pay off matrix c. unit matrix d. none 55. When both players use their optimal minimax strategies the resulting expected pay off is called a. Two person game b. zero sum game c. value of the game d. none MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 5

6 56. In a game, minimax value is maximin value a. greater than b. greater than or equal to c. less than d. none 57. In a pay off matrix the one which is the smallest value in its row and the largest value in its column is called a. saddle point b. turning point c. critical point d. none 58. The theory of games was put forward by a. Van Neumann b. Oscar Mongerstern c. both a and b d. none 59. Game theory is really the a. conflict b. science of conflict c. competition d. none 60. refers to the total pattern of choices employed by any player a. game b. action c. strategy d. none 61. Zero sum game is also referred to as a. constant sum game b. positive sum game c. negative sum game d. none of these 62. can be expressed as a LPP and vice versa a. n person game b. two person zero sum game c. 3 person game d. none of these 63. When there is no saddle point in a game, it will be the case of a. pure strategy b. no strategy c. mixed strategy d. none of these 64. Minimax principle was put forward by a. Van Neumann b. Oscar Margarsteva c. both a and b d. none 65. is the decision rule to select a particular course of action always. a. mixed strategy b. pure strategy c. strategy d. none 66. Saddle point is also called a. critical point b. turning point c. equilitarian point d. none 67. Dominance property the size of the original pay off matrix for a game having a saddle point a. increases b. reduces c. eliminate d. none MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 6

7 68. The input-output analysis technique was propounded by a. Van Neumann b. W.W. Leontief c. C.F. Christ d. none 69. Input-output analysis is concerned with only. a. cost b. production c. revenue d. none 70. An input-output model in which the entire production is consumed by those participating in the production is called a. closed b. open c. both a and b d. none 71. An input-output model in which some of the production is consumed by external bodies is called a. open b. closed c. both a and b d. none 72. Which of the following is a limitation of input-output analysis? a. unrealistic assumption b. neglects economic efficiency c. no cost adjustment d. all the above 73. In an input-output analysis, the matrix I-A is called a. identity matrix b. pay off matrix c. Leontief matrix d. none of these 74. In an input-output model, the matrix equation F = (I A) X gives the value of X as a. (A I) F b. (I A) -1 F c. (I A) X -1 d. none 75. In an input-output model, a ij = x ij / x j is called a. Leontief coefficient b. Correlation coefficient c. Technological coefficient d. None 76. When the Lorenz Curve coincides with the line of perfect equality, it indicates a. No inequality b. 100% inequality c. 50% inequality 77. A feasible solution to an LPP, which is also a basic solution to the problem is called a. Basic feasible solution b. Optimum solution c. Degenerate solution d. Infeasible solution 78. The solution to a LPP is located at one end of the a. Extreme point of the simplex b. Slack variables in the problem c. Artificial variables in the problem d. Basic solutions MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 7

8 79. Unique solution in a LP problem can be found a. Within the feasible region b. Outside the feasible region c. Corner of the feasible region d. Border of the feasible region 80. Linear programming deals with a. Minimization b. Maximization c. Minimization and maximization d. Production analysis 81. For a LPP, if there is a tie in the net evaluation row of the simplex table corresponding to an iteration a. The tie should be broken before proceeding further b. We can choose any one and proceed c. It means something has gone wrong d. The solution may cycle round 82. A LPP is infeasible, if the simplex table corresponding to the final iteration has a. A net contribution row with all zeros b. A solution column containing some artificial variables c. Both the above 83. In a LPPP, a feasible setoff solutions is one which satisfy a. The objective function b. The constraints c. Both the above 84. In linear programming the number of constraints in the dual of a given primal problem is a. The number of variables in the primal b. The number of constraints in the primal c. The number of constants in the primal 85. In a linear programming problem a. The objective function must be linear b. The constraints must be linear c. Both the objective function and constraints should be linear d. There always exist one optimal solution 86. Every basic feasible solution of LPP is of the convex set of feasible solutions. a. Maximum point b. Minimum point c. Extrimum point 87. A mathematically fair game is one in which the expected value of the game is a. One b. Negative c. Zero d. Positive MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 8

9 88. A game theory must have the following elements a. Players, strategies and pay offs b. Strategies and pay offs c. Players and pay offs d. Players and strategies 89. Strictly determined game means a. Minimax is known b. Maximin is known c. Maximin and minimax not equal d. Maximin and minimax are equal 90. A two person zero sum game has a saddle point if a. A player has one strategy, that he plays all the time b. A player can win or lose only with a value of zero c. A player chooses the alternatives with equal probability 91. A zero sum game refers to a. A game in which there are zero gain to each player b. A game in which value of the game is zero c. A game in which total gains of the games is zero 92. A constant sum game is one in which a. The total gain is constantly changing b. The total gain is indeterminate c. The total gain is fixed 93. In game theory the saddle point refers to a. The point of unstable equilibrium b. The point where corner solution is located c. The point where the minimax theorem is satisfied 94. The pay off matrix in a game refers to a. The total pay-off in a game b. The pay-off to one player in a game c. The payments made by players in a co-operative game When a two person zero sum game has no saddle point, it can have a. A solution by minimax rule b. A solution using mixed strategy c. No solution at all d. No solution by mixed strategy 96. The rule of dominance is used for a. To reduce the size of pay-off matrix b. To enlarge the size of pay-off matrix c. To make the size of pay-off table to zero. MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 9

10 97. In a dynamic Leontieff model a. Investment is explicitly model b. Investment is clubbed along with consumption c. Investment is not included 98. Given the final demand vector C and the technological matrix, A, the gross output vector X could be estimated in the input-output model as a. x = (A λi) C b. x = (I A) c c. x = (A A) -1 c d. (I A) x = c 99. In a open Leontieff input-output model, the following parameters are given a. Wages and fual demands b. Output prices b. Wages d. Input prices 100. Input-output analysis is concerned with a. Cost b. Production c. demand MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 10

11 ANSWER KEYS 1. d 2. a 3. c 4. b 5. b 6. a 7. c 8. a 9. c 10. a 11. c 12. b 13. b 14. b 15. a 16. c 17. d 18. b 19. d 20. c 21. a 22. b 23. a 24. b 25. a 26. d 27. b 28. c 29. c 30. a 31. c 32. c 33. b 34. a 35. c 36. c 37. b 38. b 39. a 40. c 41. a 42. c 43. a 44. b 45. a 46. b 47. c 48. a 49. b 50. c 51. c 52. a 53. c 54. b 55. c 56. b 57. a 58. c 59. b 60. c 61. a 62. b 63. c 64. a 65. b 66. c 67. b 68. b 69. b 70. a 71. a 72. d 73. c 74. b 75. c 76. a 77. a 78. a 79. c 80. c 81. a 82. c 83. b 84. a 85. c 86. a 87. c 88. a 89. d 90. a 91. b 92. c 93. c 94. c 95. b 96. a 97. b 98. d 99. a 100. b Reserved MATHEMATICAL ECONOMICS (II Sem BSc. Mathematics) Page 11

UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION

MATHEMATICAL ECONOMICS COMPLEMENTARY COURSE B.Sc. Mathematics II SEMESTER UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION Calicut University P. O. Malappuram, Kerala, India 67 65 40 UNIVERSITY OF CALICUT