will result in an increase in the length of the interval estimate. A. True B. False 2. The unbiased estimator of a particular parameter is unique, i.e. there can only be one unbiased estimator. A. True B. False 3. The confidence level can be interpreted as the probability that the interval estimate encloses the true population parameter. A. True B. False 4. The sample mean is the most efficient estimator of μ when sampling from the normal distribution. A. True B. False 5. If the standard error of the estimator is close to 0 then this indicates that the values of this statistic from one sample to the other are close to the value of the parameter it is estimating. A. True B. False 6. Among the class of unbiased estimators for µ, the one which has the smallest standard error is considered as the best estimator for μ A. True B. False
will result in an increase in the length of the interval estimate. A. True B. False 2. The unbiased estimator of a particular parameter is unique, i.e. there can only be one unbiased estimator. A. True B. False 3. The confidence level can be interpreted as the probability that the interval estimate encloses the true population parameter. A. True B. False 4. The sample mean is the most efficient estimator of μ when sampling from the normal distribution. A. True B. False 5. If the standard error of the estimator is close to 0 then this indicates that the values of this statistic from one sample to the other are close to the value of the parameter it is estimating. A. True B. False 6. Among the class of unbiased estimators for µ, the one which has the smallest standard error is considered as the best estimator for μ A. True B. False
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:1. Using the same sample data, increasing the confidence coefficient in interval estimation
will result in an increase in the length of the interval estimate.
A. True
B. False
2. The unbiased estimator of a particular parameter is unique, i.e. there can only be one
unbiased estimator.
A. True
B. False
3. The confidence level can be interpreted as the probability that the interval estimate
encloses the true population parameter.
A. True
B. False
4. The sample mean is the most efficient estimator of μ when sampling from the normal
distribution.
A. True
B. False
5. If the standard error of the estimator is close to 0 then this indicates that the values of this
statistic from one sample to the other are close to the value of the parameter it is estimating.
A. True
B. False
6. Among the class of unbiased estimators for μ, the one which has the smallest standard
error is considered as the best estimator for μ
A. True
B. False
7. If the computed interval estimate for µx - μy contains positive values only then we
are highly confident that the mean of X is greater than the mean of Y
A. True
B. False
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