Confidence Interval MCQs 4

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MCQs from Statistical Inference covering the topics of Estimation Confidence Interval MCQs 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 Estimation and Confidence interval MCQs will help the learner to understand the related concepts and enhance the knowledge too. Let us start with Confidence Interval MCQs

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. A single value used to estimate the value of the population parameter is called

 
 
 
 

2. A confidence interval will be widened if

 
 
 
 

3. If the population standard deviation $\sigma$ is unknown, and the sample size is small ($n\le 30$), the confidence interval for the population mean $\mu$ is based on

 
 
 
 

4. By decreasing the sample size, the confidence interval becomes

 
 
 
 

5. If the population standard deviation $\sigma$ is known, the confidence interval for the population mean $\mu$ is based on

 
 
 
 

6. A range of values calculated from the sample data and it is likely to contain the true value of the parameter with some probability is called

 
 
 
 

7. Estimation can be classified into

 
 
 
 

8. If the population standard deviation $\sigma$ is doubled, the width of the confidence interval for the population mean $\mu$ (the upper limit of the confidence interval — the lower limit of the confidence interval) will be

 
 
 
 

9. Estimates given in the form of confidence intervals are called

 
 
 
 

10. The confidence interval becomes narrow by increasing the

 
 
 
 

11. The probability associated with the confidence interval is called

 
 
 
 

12. A 95% confidence interval for the mean of a population is such that

 
 
 
 

13. The shape of the t-distribution depends upon the

 
 
 
 

14. By increasing the sample size, the precision of the confidence interval is ______.

 
 
 
 

15. The estimator is said to be _________ if the mean of the estimator is not equal to the mean of the population parameter.

 
 
 
 

16. If $(1-\alpha)$ is increased, the width of a confidence interval is

 
 
 
 

17. $(1-\alpha)$ is called

 
 
 
 

18. A statistician calculates a 95% confidence interval for $\mu$ and $\sigma$ is known. The confidence interval is RS 18000 to RS 22000, the amount of the sample mean $\overline{X}$ is

 
 
 
 

19. The distance between an estimate and the estimated parameter is called

 
 
 
 

20. The number of values that are free to vary after a certain restriction is applied to the data is called

 
 
 
 

Most of the MCQs on this page are covered from Estimate and Estimation, Testing of Hypothesis, Parametric and Non-Parametric tests, etc.

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.

Confidence Interval MCQs Estimation

Online Confidence Interval MCQs

  • Estimates given in the form of confidence intervals are called
  • $(1-\alpha)$ is called
  • If $(1-\alpha)$ is increased, the width of a confidence interval is
  • By decreasing the sample size, the confidence interval becomes
  • The confidence interval becomes narrow by increasing the
  • The distance between an estimate and the estimated parameter is called
  • By increasing the sample size, the precision of the confidence interval is _______
  • The number of values that are free to vary after a certain restriction is applied to the data is called
  • A 95% confidence interval for the mean of a population is such that A confidence interval will be widened if
  • A statistician calculates a 95% confidence interval for $\mu$ and $\sigma$ is known.
  • The confidence interval is RS 18000 to RS 22000, and the amount of the sample mean $\overline{X}$ is
  • If the population standard deviation $\sigma$ is known, the confidence interval for the population mean $\mu$ is based on
  • If the population standard deviation $\sigma$ is unknown, and the sample size is small ($n\le 30$), the confidence interval for the population mean $\mu$ is based on
  • The shape of the t-distribution depends upon the
  • If the population standard deviation $\sigma$ is doubled, the width of the confidence interval for the population mean $\mu$ (the upper limit of the confidence interval — the lower limit of the confidence interval) will be
  • A range of values calculated from the sample data and it is likely to contain the true value of the parameter with some probability is called
  • The estimator is said to be ________ if the mean of the estimator is not equal to the mean of the population parameter.
  • Estimation can be classified into
  • A single value used to estimate the value of the population parameter is called
  • The probability associated with the confidence interval is called

It is important to note that the point estimates are simpler to calculate but lack information about precision. On the other hand, interval estimates provide more information but require more calculations too, and often rely on assumptions about the data. Therefore, the choice between point estimation and interval estimation depends on the specific research question and how much detail a researcher needs about the population parameter being estimated.

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Important MCQ Sampling Quiz – 7

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The Online MCQ sampling Quiz is about the Basics of Sampling and Sampling Distributions. It will help you understand the basic concepts of sampling methods and distributions. This Online MCQ Sampling Quiz will help the students to prepare for different exams related to education or jobs. Most of the MCQs on this page cover MCQ Sampling and Sampling Distributions, Probability Sampling and Non-Probability Sampling, Mean and Standard Deviation of Sample, Sample size, Sampling error, Sample bias, Sample Selection, etc.

Please go to Important MCQ Sampling Quiz – 7 to view the test

Online MCQ Sampling Quiz

  • If $E(\overline{X})=10$ and $\mu=10$ then bias is equal to
  • If $\overline{X}=10$ and $\mu=12$ then sampling error is
  • The standard deviation of the distribution of sample means is equal to
  • If $n=25$, $\sigma^2=25$, and $\overline{X}=25$, then standard error of $\overline{X}$ will be
  • $S^2=\frac{\sum (X-\overline{X})^2}{n}$ is called
  • $s^2=\frac{\sum(X-\overline{X})^2}{n-1}$ is called
  • If $E(s^2)=3$ and $\sigma^2=2$ then bias will be
  • In sampling without replacement, the standard error of sampling distribution of sample proportion $\hat{p}$ is equal to
  • When sampling is done without replacement $\sigma_{\overline{X}}$ is equal to
  • In case of sampling with replacement $\sigma_{\hat{p}1 – \hat{p}_2}$ is equal to
  • The distribution of the means of samples of size 4, taken from a population with a standard deviation $\sigma$, has a standard deviation of
  • In sampling with replacement, $\sigma{\overline{X}_1 – \overline{X}_2}$ is equal to
  • When sampling is done with or without replacement, $E(\hat{p}_1 – \hat{p}_2)$ is equal to
  • In case of sampling with replacement, $E(S^2)$ is equal to
  • In sampling without replacement, the expected value of $S^2$ is equal to
  • When sampling is done with replacement, then $\mu{s^2}$ is equal to
  • In sampling without replacement, $\mu_{s^2}$ is equal to
  • When sampling is done with or without replacement, $\mu_{\overline{X}_1-\overline{X}_2}$ is equal to
  • If $X$ represents the number of units having the specified characteristic and $n$ is the size of the sample then sample proportion $\hat{p}$ is equal to
  • If $X$ represents the number of units having the specified characteristic and $N$ is the size of the population, then population proportion $p$ is equal to
MCQs Sampling Quiz and Sampling Distribution

MCQ sampling Quiz 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.

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Important Quiz Sampling Distribution – 6

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The Quiz Sampling Distribution is about the Basics of Sampling and Sampling Distributions. It will help you understand the basic concepts of sampling methods and distributions. This test will also help you prepare for different exams related to education or jobs. Most of the MCQs on this page cover Quiz Sampling Distribution, Probability Sampling and Non-Probability Sampling, Mean and Standard Deviation of Sample, Sample size, Sampling error, Sample bias, and Sample Selection.

Please go to Important Quiz Sampling Distribution – 6 to view the test

Online Quiz Sampling Distribution

  • If $\sigma_1=\sigma_2=\sigma$ and $n_1\ne n_2$, then S.E. ($\overline{X}2-\overline{X}_1$) is
  • In sampling with replacement, the standard error of the sample proportion $\hat{p}$ is equal to
  • If $p_1=p_2=p$ and $n_1\ne n_2$, then S.E ($\hat{p}_1 – \hat{p}_2)$ is
  • The selection of the cricket team for the World Cup is called
  • A complete list of all the sampling units is called:
  • A plan for obtaining a sample from a population is called
  • If a survey is conducted by a sampling design is called
  • The difference between the expected value of a statistic and the value of the parameter being estimated is called a
  • The standard deviation of any sampling distribution is called
  • The standard error increases when the sample size is ___________
  • The mean of sampling distribution of means is equal to
  • The mean of sampling distribution of means is equal to
  • $\frac{\text{Sum of all sample means} }{\text{Total number of samples}}$ is equal to
  • A sample which is free from bias is called
  • If $E(\overline{X})=\mu$ then bias is
  • The weight of stratum $i$ is equal to the proportion of
  • The value of $n_1$ by a proportional allocation from the following information is $N_1=580$, $N_2=140$, and $n=80$.
  • Which of the following is not a type of non-probability sampling?
  • If we have a population of 5, 4, 6, 8, and 9 and a sample size is 2, how many possible samples will be there?
  • A procedure in which the number of elements in a stratum is not proportional to the number of elements in the population is classified as
MCQs Quiz Sampling Distribution

MCQs Quiz sampling distribution 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.

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