Quantitative Techniques for Business Multiple Choice Questions
1. The techniques which provide the decision maker a systematic and powerful means of analysis to explore policies for achieving predetermined goals are called……………..
A. mathematical techniques
B. correlation technique
C. quantitative techniques
D. none of the above
Answer: C. quantitative techniques
2. Programming techniques are generally known as ……………………………..
A. statistical techniques
B. mathematical techniques
C. operation research techniques
D. none of these
Answer: B. mathematical techniques
3. ……………………………is the reverse process of differentiation
A. differential equation
B. integration
C. determinant
D. none of these
Answer: B. integration
4. ………………………… is a powerful device developed over the matrix algebra.
A. integration
B. differentiation
C. determinants
D. none of these
Answer: C. determinants
5. Correlation analysis is a……………………… analysis.
A. univariate analysis
B. bivariate analysis
C. game theory
D. queuing theory
Answer: D. queuing theory
6. When the values of two variables move in the same direction, correlation is said to be ……….
A. positive
B. negative
C. linear
D. non-linear
Answer: A. positive
7. When the values of two variables move in the opposite direction, correlation is said to be……
A. positive
B. negative
C. linear
D. non-linear
Answer: B. negative
8. When the amount of change in one variable leads to a constant ratio of change in the other variable, correlation is said to be ……………………….
A. positive
B. negative
C. linear
D. non-linear
Answer: C. linear
9. Scatter diagram is also called ……………………………..
A. correlation graph
B. zero correlation
C. probability
D. none of the above
Answer: B. zero correlation
10. If all the points of a scatter diagram lie on a straight line falling from the lower left-hand corner to the upper right-hand corner, the correlation is said to be ……………………..
A. zero correlation
B. perfect positive correlation
C. perfect negative correlation
D. high degree of positive correlation
Answer: B. perfect positive correlation
11. If all the dots of a scatter diagram lie on a straight line falling from the upper left-hand corner to the lower right hand corner, the correlation is said to be ……………………..
A. zero correlation
B. perfect positive correlation
C. perfect negative correlation
D. high degree of negative correlation
Answer: C. perfect negative correlation
12. The quantitative measure of correlation between two variables is known as………………...
A. coefficient of correlation
B. coefficient of regression
C. coefficient of determination
D. none of the above
Answer: A. coefficient of correlation
13. Coefficient of correlation measures …………………………………….
A. location
B. variability
C. concentration
D. relation
Answer: D. relation
14. Coefficient of correlation lies between ……………………………….
A. 0 and 1
B. 0 and -1
C. +1 and -1
D. none of these
Answer: C. +1 and -1
15. Karl Pearson’s coefficient of correlation is denoted by the symbol ………………
A. r
B. r
C. k
D. none of the above
Answer: B. r
16. Correlation can be ……………………………………..
A. positive only
B. negative only
C. between +1 and -1
D. positive
Answer: C. between +1 and -1
17. If r= +1, the correlation is said to be …………………..
A. perfectly positive correlation
B. high degree of correlation
C. direction and degree
D. none of the above
Answer: A. perfectly positive correlation
18. An analysis of the covariance between two or more variables is called …………………………
A. regression analysis
B. correlation analysis
C. testing of hypothesis
D. none of these
Answer: B. correlation analysis
19. In correlation analysis, P.E. = ………………..0.6745
A. standard error
B. probable error
C. coefficient of non-determination
D. coefficient of alienation
Answer: A. standard error
20. If correlation between the two variables is unity , there exists ………………………………….
A. perfect +ve correlation
B. perfect -ve correlation
C. zero correlation
D. perfect correlation
Answer: D. perfect correlation
21. In correlation analysis, the formulae 1-r2 is used to compute the value of …………………..
A. coefficient of determination
B. coefficient of non-determination
C. coefficient of correlation
D. coefficient of alienation
Answer: B. coefficient of non-determination
22. Study of correlation between two sets of data only is called …………………………
A. partial correlation
B. simple correlation
C. multiple correlation
D. none of the above
Answer: B. simple correlation
23. ………..is the study of correlation between one dependent variable with one independent variable by keeping the other independent variables as constant.
A. multiple correlation
B. simple correlation
C. partial correlation
D. none of the above
Answer: C. partial correlation
24. ……….is the study of correlation among three or more variable simultaneously.
A. multiple correlation
B. partial correlation
C. simple correlation
D. none of the above
Answer: A. multiple correlation
25. In a correlation analysis, if r=0, then we may say that, there is ………………… between variables.
A. no correlation
B. perfect correlation
C. linear correlation
D. none of the above
Answer: A. no correlation
26. Coefficient of correlation is independent of ………………………………….
A. origin
B. scale
C. both
D. none
Answer: C. both
27. When r = -1, we may say that, there is ……………………..
A. perfect negative correlation
B. high degree of negative correlation
C. 0.1
D. 2
Answer: A. perfect negative correlation
28. If the ratio of change in one variable is equal to the ratio of change in the other variable, the correlation is said to be …………………………….
A. linear
B. curvi-linear
C. non-linear
D. none of these
Answer: A. linear
29. If the plotted points of a scatter diagram fall on a narrow band, it indicates a. …………degree of correlation.
A. zero
B. low
C. high
D. none of these
Answer: C. high
30. If r =0.9, coefficient of determination is …………………….
A. 9%
B. 90%
C. absence
D. none of these
Answer: C. absence
31. If plotted points in a scatter diagram lie on a straight line vertical to the Y-axis, then r=………
A. +1
B. 0
C. -1
D. none of these
Answer: B. 0
32. …………………………..is the geometric mean of two regression coefficients.
A. coefficient of correlation
B. coefficient of standered deviation
C. arithmetic mean
D. coefficient of variation
Answer: A. coefficient of correlation
33. If dots in a scatter diagram are lie in a haphazard manner, then r= …………………..
A. 0
B. +1
C. -1
D. none of these
Answer: A. 0
34. Product moment correlation was developed by …………………..
A. karl pearson
B. charles edward spearman
C. kelly
D. none of these
Answer: A. karl pearson
35. Spearman’s coefficient of correlation is usually denoted by ……………..
A. r
B. k
C. r
D. none of these
Answer: C. r
36. If m is the coefficient of correlation, then the value of m2 is known as ……………..
A. coefficient of alienation
B. coefficient of determination
C. coefficient of non-determiantion
D. none of these
Answer: B. coefficient of determination
37. If m is the correlation coefficient, then the quantity (1-m2) is called ………………….
A. coefficient of determination
B. coefficient of non-determination
C. coefficient of alienation
D. none of these
Answer: B. coefficient of non-determination
38. The coefficient of correlation between two variables, X and Y , will have negative sign when……
A. x is increasing, y is decreasing
B. x is decreasing, y is increasing
C. any one of the above
D. none of these
Answer: C. any one of the above
39. Coefficient of concurrent deviation depends on ……………………..
A. magnitude of deviation
B. direction of deviation
C. both a and b
D. none of these
Answer: B. direction of deviation
40. ………………………. refers to analysis of average relationship between two variables to provide a mechanism for prediction.
A. correlation
B. regression
C. average
D. none of these
Answer: B. regression
41. The two regression lines coincide each other when r = …………………..
A. 0
B. -1
C. +1
D. none of these
Answer: C. +1
42. The two regression lines are mutually perpendicular when r = …………..
A. 0
B. -1
C. +1
D. none of these
Answer: A. 0
43. byx is the regression coefficient of regression equation ………………………
A. y on x
B. x on y
D. none of these
Answer: A. y on x
44. The signs of regression coefficients will be …………………..
A. different
B. same
D. none of these
Answer: B. same
45. The signs of correlation coefficient and regression coefficient are ……………………….
A. different
B. same
D. none of these
Answer: B. same
46. Scatter diagram of the various values of ( X, Y) gives the idea about …………………..
A. regression model
B. distribution of errors
C. functional relationship
D. none of the above
Answer: C. functional relationship
47. If X and Y are independent , the value of regression coefficient byx = ………………..
A. 1
B. 0
C. greater than 1
D. any negative value
Answer: B. 0
48. bxy x byx = …………………………
A. coefficient of regression
B. coefficient of regression
C. both
D. none
Answer: C. both
49. If X and Y are two variables, there can be at most ……………………..
A. three regression lines
B. two regression lines
C. one regression line
D. infinite number of regression lines
Answer: B. two regression lines
50. Geometric mean of regression coefficients will be …………………………
A. coefficient of correlation
B. coefficient of determination
C. coefficient of variation
D. none of these
Answer: A. coefficient of correlation
51. In a regression line of Y on X, the variable X is known as …………………………….
A. explanatory variable
B. independent variable
C. regressor
D. all the above
Answer: D. all the above
52. The term regression was used firstly by ………………………..
A. prof. karl pearson
B. edward spearman
D. none of these
Answer: C. 0
53. If a constant 30 is subtracted from each of the value of X and Y , the regression coefficient is
……………………..
A. reduced by 30
B. increased by 30
C. not changed
D. 1/30th of the original regression
Answer: C. not changed
54. In …………………….regression, only one independent variable is used to explain the dependent
variable.
A. linear
B. multiple
C. scatter diagram
D. none of these
Answer: A. linear
55. Regression lines are also called …………………….
A. correlation graph
B. scatter diagram
C. scatter diagram
D. none of these
Answer: C. scatter diagram
56. If the correlation between the two variables , X and Y is negative, the regression coefficient of
Y on X is ………………………..
A. zero
B. positive
C. negative
D. not certain
Answer: C. negative
57. The arithmetic mean of bxy and byx is ……………………..
A. equal to one
B. greater than r
C. francis galton
D. none of these
Answer: B. greater than r
58. The regression coefficient and correlation coefficient of two variables will be the same, if their
……………….. are same.
A. standard deviation
B. arithmetic mean
C. mean deviation
D. none of these
Answer: A. standard deviation
59. If the sign of regression coefficient bxy is negative, then the sign of regression coefficient byx will
be ……………………
A. positive
B. negative
D. none of these
Answer: B. negative
60. The square root of coefficient of determination is ……………….
A. coefficient of correlation
B. coefficient of regression
C. coefficient of variation
D. none of these
Answer: A. coefficient of correlation
61. While analysing the relationship between variables, independent variable is also
called…………………………….
A. explained variable
B. explanatory variable
C. variable
D. none of these
Answer: B. explanatory variable
62. Dependent variable is also called ……………………….
A. explained variable
B. explanatory variable
C. 4.0
D. 0.4
Answer: A. explained variable
63. If one regression coefficient is positive, the other is …………………..
A. positive
B. negative
C. zero
D. 1
Answer: A. positive
64. The arithmetic mean of bxy and byx is ………………………..
A. equal to 1
B. equal to 0
C. greater than r
D. less than r
Answer: C. greater than r
65. ………………………… refers to the chance of happening or not happening of an event.
A. regression
B. probability
C. correlation
D. none of these
Answer: B. probability
66. The numerical value given to the likelyhood of the occurrence of an event is called…………….
A. correlation
B. regression
C. probability
D. none of these
Answer: C. probability
67. Sample point is also called …………………….
A. sample space
B. elementary outcome
C. probability
D. none of these
Answer: B. elementary outcome
68. The result of a random experiment is called ……………………………
A. sample space
B. event
C. probability
D. none of these
Answer: B. event
69. ………………………. has two or more outcomes which vary in an unpredictable manner from trial to trial
when conducted under uniform conditions.
A. experiment
B. random experiment
C. probability
D. none of these
Answer: B. random experiment
70. An event whose occurrence is inevitable is called ………………………………..
A. sure event
B. impossible event
C. uncertain event
D. none of these
Answer: A. sure event
71. An event whose occurrence is impossible, is called ………………….
A. sure event
B. impossible event
C. uncertain event
D. none of these
Answer: A. sure event
72. An event whose occurrence is neither sure nor impossible, is called ………………………
A. sure event
B. impossible event
C. uncertain event
D. none of these
Answer: C. uncertain event
73. A set of events are said to be …………………. , if the occurrence of one of them excludes the
possibility of the occurrence of the other.
A. mutually exclusive
B. not mutually exclusive
C. independent
D. none of them
Answer: A. mutually exclusive
74. ………………….. refers to the arrangement of objects in a definite order.
A. combination
B. permutation
C. independent
D. none of them
Answer: B. permutation
75. Selection of objects without considering their order is called ……………………………..
A. combination
B. permutation 94. 12c12 = …………….
C. independent
D. none of them
Answer: A. combination
76. Classical probability is also called …………………….
A. priori probability
B. mathematical probability
C. finite set
D. none of these
Answer: D. none of these
77. The relative frequency approach is also called …………………………..
A. empirical approach
B. statistical probability
C. apsteriori probability
D. all the above
Answer: D. all the above
78. When P(AUB) = P(A) + P(B), then A and B are ………………………..
A. dependent
B. independent
C. mutually exclusive
D. none of these
Answer: C. mutually exclusive
79. When two events cannot occur together is called ……………………
A. equally likely
B. mutually exclusive
C. random events
D. none of these
Answer: B. mutually exclusive
80. If two sets have no common element, they are called ………………..
A. subset
B. super set
C. disjoint set
D. equal set
Answer: C. disjoint set
81. Two events are said to be ………………… , if any one of them cannot be expected to occur in
preference to the other.
A. equally likely
B. mutually exclusive
C. dependent
D. none of them
Answer: A. equally likely
82. Two events are said to be independent if ……………………
A. there is no common point in between them
B. both the events have only one point
C. each outcome has equal chance of occurrence
D. one does not affect the occurrence of the other
Answer: D. one does not affect the occurrence of the other
83. Probability of an event lies between …………………………..
A. +1 and -1
B. 0 and 1
C. 0 and -1
D. 0 and infinite
Answer: B. 0 and 1
84. Probability of sample space of a random experiment is ……………………….
A. -1
B. 0
C. +1
D. between 0 and +1
Answer: C. +1
85. In tossing a coin , getting head and getting tail are ……………………………………..
A. mutually exclusive events
B. simple events
C. complementary events
D. all the above
Answer: A. mutually exclusive events
86. If two events, A and B are mutually exclusive, then P(AUB) = …………………….
A. p(a) + p(b)
B. p(a) + p(b) – p(a and b)
C. p(a) + p(b) + p(a and b)
D. none of these
Answer: A. p(a) + p(b)
87. If two events, A and B are not mutually exclusive, the P(AUB) = ………………
A. p(a) + p(b)
B. p(a) + p(b) – p(a and b)
C. p(a) + p(b) + p(a and b)
D. none of these
Answer: B. p(a) + p(b) – p(a and b)
88. An event consisting of those elements which are not in the given event is called………….
A. simple event
B. derived event
C. complementary event
D. none of these
Answer: C. complementary event
89. The definition of priori probability was originally given by ……………………….
A. de-moivre
B. laplace
C. pierre de fermat
D. james bernoulli
Answer: B. laplace
90. …………………… refers to the totality of all the elementary outcomes of a random experiment.
A. sample point
B. sample space
C. simple event
D. none of these
Answer: B. sample space
91. The sum of probabilities of all possible elementary outcomes of a random experiment is
always equal to ……………….
A. 0
B. 1
C. infinity
D. none of these
Answer: B. 1
92. Chance for an event may be expressed as ……………..
A. percentage
B. proportion
C. infinity
D. none of these
Answer: D. none of these
93. If it is known that an event A has occurred, the probability of an event B given A is called
……………………….
A. empirical probability
B. conditional probability
C. priori probability
D. posterior probability
Answer: B. conditional probability
94. The mean of a binomial distribution is ………………………
A. np
B. npq
C. square root of npq
D. none of these
Answer: A. np
95. Binomial distribution is a ………………………….. probability distribution
A. discrete
B. continuous
C. continuous distribution
D. none of these
Answer: A. discrete
96. Binomial distribution is originated by …………………………….
A. prof. karl pearson
B. simeon dennis poisson
C. james bernoulli
D. de-moivre
Answer: C. james bernoulli
97. When probability is revised on the basis of all the available information, it is called ………….
A. priori probability
B. posterior probability
C. continuous
D. none of these
Answer: B. posterior probability
98. Baye’s theorem is based upon inverse probability.
A. yes
B. no
C. probability
D. none of these
Answer: A. yes
99. Probability distribution is also called theoretical distribution.
A. yes
B. no
C. probability
D. none of these
Answer: A. yes
100. The height of persons in a country is a …………………….. random variable.
A. discrete
B. continuous
C. discrete as well as continuous
D. neither discrete nor continuous
Answer: B. continuous
101. Random variable is also called …………………………
A. stochastic variable
B. chance variable
C. both
D. none of these
Answer: C. both
102. If the random variable of a probability distribution assumes specific values only, then it is
called ………………………….
A. discrete probability distribution
B. continuous probability distribution
C. probability distribution
D. none of these
Answer: A. discrete probability distribution
103. npq is the variance of ………………………………
A. binomial distribution
B. poisson distribution
C. probability distribution
D. none of these
Answer: A. binomial distribution
104. For a binomial distribution with probability p of a success and of q of a failure, the relation
between mean and variance is ………………………..
A. mean is less than variance
B. mean is greater than variance
C. mean is equal to variance
D. mean is greater than or equal to variance
Answer: B. mean is greater than variance
105. In a binomial distribution, if n =8 and p = 1/3, then variance = ……………………
A. 8/3
B. 48/3
C. 64/3
D. 16/9
Answer: D. 16/9
106. In a ………………………… distribution, mean is equal to variance
A. binomial
B. poisson
C. normal
D. gamma
Answer: B. poisson
107. For a binomial distribution, the parameter n takes …………………. values
A. finite
B. infinite
C. continuous
D. none of these
Answer: A. finite
108. Poisson distribution is the limiting form of ………………………….
A. binomial distribution
B. normal distribution
C. poisson
D. none of these
Answer: A. binomial distribution
109. Poisson distribution is originated by ……………………..
A. de-moivre
B. bernoulli
C. poisson
D. none of these
Answer: C. poisson
110. In Poisson distribution, mean is denoted by ……………………
A. npq
B. np
C. m
D. e
Answer: C. m
111. Poisson distribution is a ……………………… distribution.
A. negatively skewed distribution
B. positively skewed distribution
C. symmetrical distribution
D. none of these
Answer: B. positively skewed distribution
112. In Poisson distribution, the value of ‘e’ = ……………………..
A. 2.178
B. 2.817
C. 2.718
D. 2.871
Answer: C. 2.718
113. Mean and variance of Poisson distribution is equal to ………………………….
A. m
B. e
C. np
D. npq
Answer: A. m
114. If two independent random variables follow binomial distribution, their sum follows…………..
A. binomial distribution
B. poisson distribution
C. normal distribution
D. none of these
Answer: A. binomial distribution
115. When X follows binomial distribution, P(X=0) is…………………….
A. 0
B. 1
C. qn
D. pn
Answer: C. qn
116. Normal distribution was first discovered by …………………………….. in 1733 as limiting form of
binomial distribution.
A. karl pearson
B. james bernoulli
C. de-moivre
D. simeon denis poisson
Answer: C. de-moivre
117. Normal distribution is a……………………… probability distribution.
A. discrete
B. continuous
C. poisson
D. none of these
Answer: B. continuous
118. ………………………distribution gives a normal bell shaped curve.
A. normal
B. poisson
C. binomial
D. none of these
Answer: A. normal
119. The normal curve is ……………………………
A. bi-model
B. uni-model
C. mean
D. none of these
Answer: B. uni-model
120. Normal distribution is ………………….
A. continuous
B. unimodal
C. normal
D. none of these
Answer: D. none of these
121. For a normal curve , the QD, MD, and SD are in the ratio of …………………………
A. 5:8:10
B. 10:12:15
C. 2:3:5
D. none of these
Answer: B. 10:12:15
122. An approximate relation between QD and SD of normal distribution is ……………
A. 2qd = 3sd
B. 5qd = 4sd
C. 4qd = 5sd
D. 3qd = 2sd
Answer: D. 3qd = 2sd
123. An approximate relation between MD about mean and SD of a normal distribution is
……………………….
A. 5md = 4 sd
B. 3md = 3 sd
C. 3md = 2 sd
D. 4md = 5 sd
Answer: A. 5md = 4 sd
124. The area under the standard normal curve beyond the line z = ±1.96 is ………………………….
A. 5%
B. 10%
C. 90%
D. 95%
Answer: A. 5%
125. Normal distribution is …………………………..
A. mesokurtic
B. leptokurtic
C. more than 0
D. in between +1 and -1
Answer: A. mesokurtic
126. Mean Deviation (M.D) for normal distribution is equal to ………………….
A. 5/4 s.d.
B. 3/2 s.d.
C. 4/5 s
Answer: C. 4/5 s
127. In a ……………………. distribution, quartiles are equi-distant from median.
A. binomial
B. poisson
C. normal
D. none of these
Answer: C. normal
128. A normal distribution requires two parameters, namely the mean and …………..
A. median
B. mode
C. standard deviation±
D. mean deviation
Answer: C. standard deviation±
129. A normal distribution is an approximation to …………………………
A. binomial distribution
B. poisson distribution
C. poisson
D. none of these
Answer: A. binomial distribution
130. Mean ± 2 S.D. covers ………….. % area of normal curve.
A. 68.27
B. 95.45
C. 95.54
D. 98.73
Answer: B. 95.45
131. Theoretically, the range of normal curve is …………………………………………
A. -1 to +1
B. +1 to infinity
C. –infinity to +infinity
D. none of these
Answer: C. –infinity to +infinity
132. Standard deviation of the sampling distribution is called ……………………….
A. probable error
B. standard error
C. mean deviation
D. coefficient of variation
Answer: B. standard error
133. Index numbers are
A. special type of average
B. measure the economic changes
C. to measure relative changes
D. all of these
Answer: D. all of these
134. The techniques which provide the decision maker a systematic and powerful means of
analysis to explore policies for achieving predetermined goals are called……………..
A. Mathematical techniques
B. Correlation technique
C. Quantitative techniques
D. . None of the above
Answer: C. Quantitative techniques
135. ……………………….. is the reverse process of differentiation
A. Differential equation
B. Integration
C. Determinant
D. None of these
Answer: B. Integration
136. ………………………….is an operation research technique which resembles a real life
situation.
A. Decision theory
B. Simulation
C. Game theory
D. Queuing theory
Answer: B. Simulation
137. C.P.M. stands for………………………………………………….
A. Critical Process Method
B. Critical Performance Measurement
C. Critical Path Method
D. Critical Programme Method
Answer: C. Critical Path Method
138. The word correlation usually implies………………………..
A. Cause and effect relationship
B. Mutual interdependence
C. Both
D. None of the above
Answer: C. Both
139. Correlation analysis is a ……………………….analysis.
A. Univariate analysis
B. Bivariate analysis
C. Multivariate analysis
D. Both b and c
Answer: D. Both b and c
140. When the values of two variables move in the same direction, correlation is said to be
……….
A. Positive
B. Negative
C. Linear
D. Non-linear
Answer: A. Positive
141. When the values of two variables move in the opposite direction, correlation is said to be
……………………
A. Positive
B. Negative
C. Linear
D. Non-linear
Answer: B. Negative
142. A _________ is a decision support tool that uses a tree-like graph or model of decisions
and their possible consequences, including chance event outcomes, resource costs, and utility.
A. Decision tree
B. Graphs
C. Trees
D. Neural Networks
Answer: A. Decision tree
143. What is Decision Tree?
A. Flow-Chart
B. Structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label
C. Flow-Chart & Structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label
D. None of the mentioned
Answer: C. Flow-Chart & Structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label
144. Choose from the following that are Decision Tree nodes?
A. Decision Nodes
B. End Nodes
C. Chance Nodes
D. All of the above
Answer: D. All of the above
145. Decision Nodes are represented by ——
A. Disks
B. Squares
C. Circles
D. Triangles
Answer: B. Squares
146. Chance Nodes are represented by __________
A. Disks
B. Squares
C. Circles
D. Triangles
Answer: C. Circles
147. Which of the following are the advantage/s of Decision Trees?
A. Possible Scenarios can be added
B. Use a white box model, If given result is provided by a model
C. Worst, best and expected values can be determined for different scenarios
D. All of the above
Answer: D. All of the above
148. —– are the whose values are to be determined from the solution of the LPP
A. Objective function
B. Decision variables
C. Constrains
D. Opportunity cost
Answer: B. Decision variables
149. ———— specifies the objective or goal of solving the LPP
A. Objective function
B. Decision variables
C. Constraints
D. Opportunity cost
Answer: A. Objective function
150. Objective function is expressed in terms of the ————–
A. Numbers
B. Symbols
C. Decision variables
D. None of the above
Answer: C. Decision variables
151. ———- are the restrictions or limitations imposed on the LPP
A. Variables
B. Cost
C. Profit
D. Constraints
Answer: D. Constraints
152. Region of feasible solution in LPP graphical method is called
A. Infeasible region
B. Unbounded region
C. Infinite region
D. Feasible region
Answer: D. Feasible region
153. When it is not possible to find solution in LPP, it is called as case of ———
A. Unknown solution
B. Unbounded solution
C. Infeasible solution
D. Improper solution
Answer: C. Infeasible solution
154. When the feasible region is such that the value of objective function can extended to infinity, it is called a case of ————
A. Infeasible region
B. Alternate optimal
C. Unbounded solution
D. Unique solution
Answer: C. Unbounded solution
155. When the constraints are a mix of ‘less than’ and ‘greater than’ it is called a problem having
A. Multiple constraints
B. Infinite constraints
C. Infeasible region
D. Mixed constraints
Answer: D. Mixed constraints
156. In linear programming, unbounded solution means ————–
A. Infeasible region
B. Degenerate solution
C. Infinite solution
D. Unique solution
Answer: C. Infinite solution