MCQ 6

           MCQ 6                       

26.    A consistent estimator must be

 A.          Asymptotically unbiased.

 B.          Asymptotically biased.

 C.          Asymptotically   sufficient.

 D.          Asymptotically clear.

27.    The probability of rejection of the null hypothesis is called

          A.           Probability function.

          B.           Inverse function.

  C.           Power function.

  D.           Sin function.

28.    The test with largest "1 -B"    is called

A.            Most powerful test.

B.            Least powerful test.

C.            Powerful test. 

D.           Simple test.   

29.    The critical region based on most powerful test is called

         A.          Powerful critical region.

 B.          Best critical region.

 C.          Complete critical region.

 D.          First critical region.

30.    Best critical region gives

          A.          Minimum 1 -B.

          B.          Smallest 1 -B.

 C.           Maximum 1 -B.

 D.           Different 1 -B.         

31.    Neyman Pearson Lemma is used to test

          A.        Complex hypothesis.

          B.        Only null hypothesis.

          C.        Only alternative hypothesis

          D.        Simple hypothesis.

32.    Neyma Pearson Lemma guarantees to provide maximum power of test for

A.         Fixed size of critical region.

B.         Variable size of critical region.

C.         Small size of critical region. 

D.         Large size of critical region.

33.    In testing a simple H_o Vs a simple H₁, it fallows that if a BCR exits then it is a function of

        A.             Statistics

B.             Sufficient statistic.

C.             Efficient statistic.

D.             Consistent statistic

34.    In decision (inference) theory an estimator is known as

A.            Decision function.

B.            Decided function,

C.            Undecided function.

D.            Sufficient function.

35.    The difference b/w an estimator and the true value are known as

        A.            “Residual” which is to be estimated.

B.            “Loss” which is the error.

C.            “Difference” which is standard error.

D.            “Deviation” which is fluctuation.

36.    A loss function will be

          A.         Function of statistic.

          B.         Function of parameter.

          C.         Function of variance.

  D.         Function of error.

37.    The expected value of loss function is called

A.          Risk function.

B.          Decision function.

C.          Minimax.

D.          Inverse function

38.    Bayes risk is

        A.         An expected risk.

        B.         Minimum risk

C.         An average risk.

D.         Maximum risk.

                   

39.    Bayes estimator is that estimator which has

         A.        Largest risk.

         B.        Smallest risk.

         C.        Unexpected risk.

         D.        Maximum risk.

40.    For absolute loss function, the Bayes estimator is given by median of the

         A.       Prior distribution.

         B.       Binomial distribution.

 C.       Posterior distribution.

 D.       Distribution.

41.   Sometimes we are required to compare several population means simultaneously. This is also possible by using two sample t- test ,

A.       But will take large time.

B.       But the result will be not reliable.

C.       The result will be just an approximation.

D.       Involves too many formulae.

42.  Improper distribution is that distribution whose pdf may be not a proper pdf  i.e. whose area under the curve may not be

        A.        Straight line.

B.        Unity.

C.         50%

D.         A square.

43.   An estimator whose maximum risk is smaller than the maximum risk of any other estimator is called

A.       Minimax estimator.

B.       Minimum risk estimator.

C.       Maximum risk estimator.

D.       Maximax estimator.

44.  If the posterior distribution is turned like to be the prior distribution, it is called

        A.      Conjugate type.

B.      Prior conjugate type.

C.      Posterior conjugate type.

D.      Posterior conjugate type.

45.  Inference based on the posterior distribution is not unique, because we have to use different

          A.      Posterior distributions.

          B.      Frequency distributions.

          C.      Multinomial distributions.

  D.      Prior distributions.

46.  There are two types of experiments, comparative experiments and

          A.     Random experiments.

          B.     Non random experiments.

          C.     Simple experiments.

  D.     Factorial experiments.

47.   An experiment in which we compare two or more than two factors

A.    Comparative experiment.

        B.    Non random experiments.

        C.    Simple experiments

D.    Factorial experiments

48.   The experiment, in which we measure not only the individual effects but the interaction effects are also investigated.

 A.      Comparative experiment.

         B.      Non random experiment.

 C.      Factorial experiment.

 D.      Random experiment.

49.   A factorial experiment in which all factors occur with same number of levels is called

 A.      Symmetrical factorial experiment.

 B.      Square experiment.

 C.      Circular experiment

 D.     Square and symmetrical experiment.

50.   A factorial experiment in which all the factors not occur        with same number of levels is called

 A.      Symmetrical factorial experiment.

 B.      Square experiment.

 C.      Asymmetrical factorial experiment.

 D.      Circular experiment.

26	A	27	C	28	A	29	B	30	C
31	D	32	A	33	B	34	A	35	B
36	D	37	A	38	C	39	B	40	C
41	A	42	B	43	A	44	B.	45	D
46	D	47	A	48	C	49	A	50	C