# MCQs Sampling and Sampling Distribution Quiz 11

Online Sampling Distribution Quiz with Answers for the preparation of exams and different statistical job tests in Government/ Semi-Government or Private Organization sectors. This Online Quiz about Sampling Distributions is also helpful in getting admission to various colleges and Universities. There are 20 Multiple Choice Type Questions from the Sampling and Sampling Distribution Quiz. Let us start with the Sampling Distribution Quiz.

1. When sampling is done with or without replacement, $E(\overline{y})$ is equal to

2. A procedure in which the number of elements in a stratum is proportional to the number of elements in the population is called

3. When the procedure of selecting the elements from the population is not based on probability is known as:

4. Which one of these sampling methods is a probability method?

5. The university has 5000 students belonging to the following classes: (i) 1500 are freshmen, (ii) 1200 are sophomores, (iii) 1400 are juniors, and (iv) 900 are seniors. The university administration wants to get an estimate of all the student’s views on a proposal to help alleviate the parking problem on campus. Suppose, that a sample of 100 students is chosen, what is the required sample size for the freshman stratum under proportional allocation?

6. The weight of the stratum is equal to the proportion of:

7. Stratification is to produce estimators with small

8. The value of $n_2$ by a proportional allocation from the following information is:
$N_1=580$, $N_2=140$ and $n=80$.

9. Which one of the following is the benefit of using simple random sampling?

10. Consider a population of size 700 consisting of three strata such that $N_1=100, N_2=250$, and $N_3=350$. The required sample size is 18. What will be the sample size for stratum-II according to proportional allocation?

11. A group consists of 300 people and we are interviewing all members of a given group called:

12. Which one of the following is the main problem with using non-probability sampling techniques?

13. If a researcher randomly samples 100 observations in each population category then his ————— sample will be ———-.

14. When the sample size increases, everything else remains the same, and the width of a confidence interval for a population parameter will

15. When the number of observations drawn from a stratum is small relative to the overall size of the stratum then the ————- will also be small.

16. The weight of the stratum is equal to the proportion of

17. Sampling in which a sampling unit can be repeated more than once is called

18. Consider a population of size 700 consisting of three strata such that $N_1=100, N_2=250$, and $N_3=350$. The required sample size is 18. What will be the sample size for stratum-III according to proportional allocation?

19. The margin of error is the level of _________ you require.

20. Regardless of the difference in the distribution of the sample and population, the mean of sampling distribution must be equal to

### MCQs Sampling Distribution Quiz with Answers

• The weight of the stratum is equal to the proportion of:
• A group consists of 300 people and we are interviewing all members of a given group called:
• When the procedure of selecting the elements from the population is not based on probability is known as:
• The university has 5000 students belonging to the following classes: (i) 1500 are freshmen, (ii) 1200 are sophomores, (iii) 1400 are juniors, and (iv) 900 are seniors. The university administration wants to get an estimate of all the student’s views on a proposal to help alleviate the parking problem on campus. Suppose, that a sample of 100 students is chosen, what is the required sample size for the freshman stratum under proportional allocation?
• When the sample size increases, everything else remains the same, and the width of a confidence interval for a population parameter will
• The value of $n_2$ by a proportional allocation from the following information is: $N_1=580$, $N_2=140$ and $n=80$.
• Sampling in which a sampling unit can be repeated more than once is called
• Which one of these sampling methods is a probability method?
• Which one of the following is the main problem with using non-probability sampling techniques?
• Which one of the following is the benefit of using simple random sampling?
• When sampling is done with or without replacement, $E(\overline{y})$ is equal to
• The margin of error is the level of _ you require.
• If a researcher randomly samples 100 observations in each population category then his ————— sample will be ———-.
• Stratification is to produce estimators with small
• The weight of the stratum is equal to the proportion of
• When the number of observations drawn from a stratum is small relative to the overall size of the stratum then the ————- will also be small.
• Regardless of the difference in the distribution of the sample and population, the mean of sampling distribution must be equal to
• A procedure in which the number of elements in a stratum is proportional to the number of elements in the population is called
• Consider a population of size 700 consisting of three strata such that $N_1=100, N_2=250$, and $N_3=350$. The required sample size is 18. What will be the sample size for stratum-II according to proportional allocation?
• Consider a population of size 700 consisting of three strata such that $N_1=100, N_2=250$, and $N_3=350$. The required sample size is 18. What will be the sample size for stratum-III according to proportional allocation?

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A sampling distribution depends on several factors:

• The statistic being used: Is the researcher looking at the mean, median, or something else?
• The original population’s distribution: Is the population data normally distributed, skewed, or something else?
• Sample size: Generally, larger samples lead to sampling distributions closer to the actual population distribution.

In conclusion, sampling distributions are vital tools in statistics. Sampling Distributions help us to understand the variability of statistics calculated from samples and make informed inferences about the population from which the samples were drawn.