Statistical Inference
If X follows normal distribution ( ) then Var ( ) =
n /(n+1)2
/(n+1)2
Both A and B
Sufficient
n /(n+1)2
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Neyman Fisher Factorization theorem is also known as:A. Theorem of sufficient estimators
B. Rao Black-well theorem
C. Estimator
D. None of these
Mean square of an estimator is equal to:
A. Variance + (Bias)2
B. E(x) + (Bias)2
C. (Bias)2
D. Variance
If expected value of an estimator is equal to its respective parameter then this property known is:
A. Biasedness
B. Estimation
C. Unbiasedness
D. Both B and C
In case of unbiased estimators, the estimator having minimum variance is called an:
A. Efficient estimator.
B. Sufficient
C. Both A and B
D. Consistent
Statistic may be an:
A. Estimator
B. Estimate
C. Both A and B
D. None of these
If then the statistic โtโ is called:
A. Complete
B. Unbiased
C. Both A and B
D. Sufficient
In Cramer-Rao Inequality var (T) is called:
A. Complete
B. Minimum variance bond
C. Efficient
D. None of these
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