# MCQs Estimation 6

MCQs Estimation Quiz covers the topics of Estimation for the preparation of exams and different statistical job tests in Government/ Semi-Government or Private Organization sectors. These quizzes help get admission to different colleges and Universities. The MCQs Estimation Quiz will help the learner to understand the related concepts and enhance the knowledge too.

MCQs about statistical inference covering the topics estimation, estimator, point estimate, interval estimate, properties of a good estimator, unbiasedness, efficiency, sufficiency, Large sample, and sample estimation.

1. An Estimator $\hat{T}$ is an unbiased estimator of the population parameter $T$ if

2. By the method of moments, one can estimate:

3. Since $E(X)=$______. $X$ is said to be an unbiased estimator of the population mean.

4. A quantity obtained by applying a certain rule or formula is known as

5. The consistency of an estimator can be checked by comparing

6. The estimation and testing of the hypothesis are the main branches of ________.

7. Sample median as an estimator of the population mean is always

8. If $\alpha=0.10$ and $n=15$ then $t_{\frac{\alpha}{2}}$ will be

9. Criteria to check a point estimator to be good are

10. If $n_1=16$, $n_2=9$ and $\alpha=0.01$, then $t_{\frac{\alpha}{2}}$ will be

11. The sample proportion $\hat{p}$ is ______ estimator

12. Roa-Blackwell Theorem enables us to obtain minimum variance unbiased estimator through:

13. _______ is the value of a sample statistic.

14. ________ is an estimate expressed by a single value.

15. An estimator $T_n$ is said to be a sufficient statistic for a parameter function $\tau(\theta)$ if it contains all the information which is contained in the:

16. Crammer-Rao inequality is valid in the case of:

17. If the sample average $\overline{x}$ is an estimate of the population mean $\mu$, then $\overline{x}$ is:

18. Sampling error decreases by ______ the sample size.

19. A _____ is the specific value of the statistics used to estimate the population parameter.

20. For an estimator to be consistent, the unbiasedness of the estimator is

Statistical inference is a branch of statistics in which we conclude (make wise decisions) about the population parameter by making use of sample information. Statistical inference can be further divided into the Estimation of parameters and testing of the hypothesis.

Estimation is a way of finding the unknown value of the population parameter from the sample information by using an estimator (a statistical formula) to estimate the parameter. One can estimate the population parameter by using two approaches (I) Point Estimation and (ii) Interval Estimation.
In point Estimation, a single numerical value is computed for each parameter, while in interval estimation a set of values (interval) for the parameter is constructed. The width of the confidence interval depends on the sample size and confidence coefficient. However, it can be decreased by increasing the sample size. The estimator is a formula used to estimate the population parameter by making use of sample information.

### Online MCQs Estimation with Answers

• Criteria to check a point estimator to be good are
• By the method of moments, one can estimate:
• If the sample average $\overline{x}$ is an estimate of the population mean $\mu$, then $\overline{x}$ is:
• A quantity obtained by applying a certain rule or formula is known as
• The consistency of an estimator can be checked by comparing
• For an estimator to be consistent, the unbiasedness of the estimator is
• Sample median as an estimator of the population mean is always
• Roa-Blackwell Theorem enables us to obtain minimum variance unbiased estimator through:
• An estimator $T_n$ is said to be a sufficient statistic for a parameter function $\tau(\theta)$ if it contains all the information which is contained in the:
• Crammer-Rao inequality is valid in the case of:
• If $n_1=16$, $n_2=9$ and $\alpha=0.01$, then $t_{\frac{\alpha}{2}}$ will be
• If $\alpha=0.10$ and $n=15$ then $t_{\frac{\alpha}{2}}$ will be
• A _ is the specific value of the statistics used to estimate the population parameter.
• An Estimator $\hat{T}$ is an unbiased estimator of the population parameter $T$ if
• Since $E(X)=$_______. $X$ is said to be an unbiased estimator of the population mean.
• The sample proportion $\hat{p}$ is ________ estimator Sampling error decreases by the sample size.
• __________ is the value of a sample statistic.
• __________ is an estimate expressed by a single value.
• The estimation and testing of the hypothesis are the main branches of ________.

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