MCQ 7

MCQ 7

51.  When all possible combination of factors levels are tested once, then experiment is called full factorial or complete or

        A.        One double replicate.

B.        A single replicate.

C.        A double replicate.

D.        First replicate.

52.   If each combination is tested several times, the experiment is called a

A.         Triple replicate.

B.         Multiple replicate.

C.         Replication.

D.         Duplication.

53.   If not all the combinations of factors levels are tested, the experiment is called fractional factorial or incomplete factorial experiment.

          A.        True.

          B.         False.

          C.         Sometimes true.

          D.         Confusing.

54    Whenever experiment involves sub sampling, there are two types of variability in the experimental error i.e. ε_ijk and δ_ijk.

      (i) ε_{ijk i.e. variation among experimental units on the same   treatment}

     (ii)  δ_ijk  i.e. variation among sampling units within the

A.          Experimental units.

B.           Treatments.

C.            Events.

D.           Distribution

55.   The set of operations which potentially affect the change in the experimental units i.e. a crop variety, a dose of fertilizer, combination of factor levels etc.

          A.        An applicator.

          B.        A dose.

  C.        An event.

          D.        A treatment.

56.  The smallest part of experimental material to which one trial of a single treatment is applied e.g. a plot, an area of ground containing many plots, an animal or several animals.

          A.        Medicine.

          B.         Experimental unit.

          C.         Dose.

          D.         Design.

57    The fraction of experimental unit and the smallest part of experimental material to which we can make a single measurement.

A.             Sampling unit.

B.              Treatment.

C.              Dose.

D.             Design.

58.    A plan and set of rules which is used to test the association between the experimental unit and treatments such that we can measure yield i.e.

               Yield= True value + error.

          A.     Model.

          B.     Design.

          C.     Formula.

          D.     Relation.

59.      The principles of design are replication, randomization and

          A.      Neutralization.

          B.      Summarization.

  C.      Reduction of error.

  D.      Random error.

60.    If a treatment is used more than once in an experiment under identical conditions then we say that the treatment is

          A.       Repeated.

          B.       Retreated.

  C.       Replicated.

  D.       Recycled.

61.    The process of assigning treatments to the experimental units in such a way that all the units have an equal chance of receiving a treatment.

        A.       Randomization.

B.       Neutralization.

C.       Summarization.

D.       Reduction of error.

62.      Reduction of error is possible by

          A.        By using formula.

  B.        Local control or blocking.

  C.        By using calculator.

  D.        By introducing new techniques.

63.      Blocks are always made orthogonal (perpendicular) of variation.

          A.        In case of frequency distribution.

          B.        In case of non parametric.

          C.        In case of binomial distribution.

          D.        In case of designs

64.       Each block contains

A.       Homogeneous experimental units.

B.       Heterogeneous experimental units.

C.        Frequency.

D.        Elements.

65.       Each treatment occurs once in

        A.          Each table.

        B.          Each row.

        C.          Each column.

D.          Each block.

66.     Model is just scientific way of

        A.        Discussing a phenomenon.

B.        Describing a data.

C.        Picturing facts.

D.        Calculations

67.    A relation among some constants and variables.

          A.         Calculation.

          B.         Rule.

          C.         Model.

          D.        Equation.

68     k treatments are specifically chosen by the experimenter.

          A.        In a random effect model.

          B.        In a fixed effect model.

          C.        In a mixed effect model.

          D.        In a rare effect model.

69.    Hypothesis about treatment mean is tested and conclusion is drawn only for k treatments.

  A.       In a random effect model.

          B.        In a fixed effect model.

          C.        In a mixed effect model.

          D.        In a rare effect model.

 

70.   When we want to compare two population means, we use

         A.          Any formula.

         B.          Any estimator.

         C.          Any equation.

 D.         Two sample t-test.

71.    Is there any relationship between CRD and student t-test?

          A.      No.

          B.      Yes.

          C.      Some times.

          D.     Strange.

                              

72.    In a random effect model, the k treatments used in the experiment, are chosen

A.       Randomly.

B.       Non randomly.

C.       Through a formula.

D.       Randomly but in advance.

73.    In case of random effect model, hypothesis about variation among treatment

          A.       Variance is tested.

          B.       Standard deviation is tested.

  C.       Mean is tested.

  D.       Geometric mean is tested.

            

74.    In some experiments situation it is inconvenient to measure yield on the entire experimental unit. In this case we use the method of

A.       Rank correlation.

B.       Extrapolation.

C.       Interpolation.

D.       Hierarchical classification.

     

75.      In the situation in which both fixed effect and random effect phenomena exists, are called

A.        Random effect model.

        B.        Fixed effect model.

        C.        Rare effect model.

        D.        Mixed effect model.

51	B	52	B	53	A	54	A	55	D
56	B	57	A	58	B	59	C	60	C
61	A	62	B	63	D	64	A	65	D
66	B	67	C	68	B	69	B	70	D
71	B	72	A	73	C	74	D	75	D