MCQs Estimation Quiz 7

MCQs from Statistical Inference cover the topics of Estimation and Hypothesis Testing for the preparation of exams and different statistical job tests in Government/ Semi-Government or Private Organization sectors. These tests are also helpful in getting admission to different colleges and Universities. The online estimation quiz MCQs will help the learner to understand the related concepts and enhance the knowledge too.

Most of the MCQs on this page are covered from Estimate and Estimation, Testing of Hypothesis, Parametric and Non-Parametric tests, etc. Let’s start with the MCQs quiz of estimation with answers.

Online MCQs Estimation Test

1. If the population Standard Deviation is unknown and the sample size is less than 30, then Confidence Interval for the population mean ($\mu$) is

2. In a $Z$-test the number of degrees of freedom is

3. If $1-\alpha=0.90$ then value of $Z_{\frac{\alpha}{2}}$ is

4. A sample is considered a small sample if the size is

5. By decreasing $\overline{X}$ the length of the confidence interval for $\mu$

6. The width of confidence interval decreases if the confidence coefficient is

7. A statistician calculates a 95% confidence interval for $\mu$ when $\sigma$ is known. The confidence interval is Rs 18000 to 22000, and then amount of sample means $\overline{X}$ is:

8. A large sample contains more than

9. In applying t-test

10. For $\alpha=0.05$, the critical value of $Z_{0.05}$ is equal to

11. t-distribution is used when

12. If $\mu=130, \overline{X}=150, \sigma=5$, and $n=10$. What Statistic is appropriate.

Statistical inference is a branch of statistics in which we draw conclusions (make some wise decisions) about the population parameter by using sample information. Statistical inference can be further divided into Estimation of the Population 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 an 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.