# Sampling Design Techniques Quiz

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Welcome to a fantastic Sampling design techniques quiz. Here are some Trivia Questions on Sampling Design. When it comes to sampling, a person needs to have the correct sample with the same characteristics as the entire population for the results to be the same. Take up the quiz and see if you understand the sampling techniques that you will be expected to use in the field. All the best to you!

• 1.

### What is the main difference between probability and non-probability sampling?

• A.

Probability sampling involves the need for the computation of a sample via certain equations.

• B.

Non-probability sampling is preferred in qualitative research.

• C.

Randomization is involved in probability sampling.

• D.

Non-probability sampling is more appropriate for interviews.

C. Randomization is involved in probability sampling.
Explanation
The main difference between probability and non-probability sampling is that the latter selects the elements of the sample by choice and not by instead of by chance.

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• 2.

### During the conduct of his survey, Lucas chose his respondents by ensuring that they were those who could provide him with the needed data for his study. The type of non-probability sampling that he utilized is known as:

• A.

Convenience sampling

• B.

Judgment sampling

• C.

Snowball sampling

• D.

Quota sampling

B. Judgment sampling
Explanation
Lucas chose his respondents based on their ability to provide him with the needed data for his study, indicating that he purposefully selected individuals who he believed would have relevant information. This type of sampling is known as judgment sampling, where the researcher uses their own judgment to select participants who they believe will be most informative for the study.

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• 3.

### Which among the following formulas is relevant towards systematic random sampling?

• A.

K = N / n

• B.

N = N / k

• C.

N = (Ni / N) (n)

• D.

K = (N)(N) / 2n

A. K = N / n
Explanation
The kth element in systematic random sampling is computed by dividing the population by the desired sample.

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• 4.

### Engelbert chooses the elements for his sample by giving particular attention to each sub-population. He sees to it that every computed stratum sample is the same as the other strata and that the respondents are chosen randomly. What sampling design is used?

• A.

Systematic random sampling

• B.

Stratified random sampling with equal allocation

• C.

Stratified random sampling with proportional allocation

• D.

Cluster sampling

B. Stratified random sampling with equal allocation
Explanation
Stratified random sampling comes in handy when researchers prefer to consider the strata for the population. This ensures that each stratum has adequate respondents either of equal number to the other strata or having it in proportion to its respective population stratum.

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• 5.

### A sampling technique is used in Qualitative research wherein the researcher chooses individuals who are easily accessible to become respondents for the study.

• A.

Judgment Sampling

• B.

Convenience Sampling

• C.

Snowball Sampling

• D.

Quota Sampling

B. Convenience Sampling
Explanation
Although easy to utilize, convenience sampling poses a threat to the reliability of the results due to sampling bias. This may be an option as a last resort when researchers face problems in data gathering which can not be addressed.

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• 6.

### Michael wanted to have an equal allocation of units per sample of each stratum for a population of 352. The following are the subpopulation for each stratum: Chinese 125, Japanese 84, Filipino 94, and Korean 49. How many samples for each stratum would be needed?

• A.

37

• B.

47

• C.

57

• D.

67

B. 47
Explanation
The following is the formula for stratified random sampling with equal allocation:

n (subscript i) = n / k

where:
n (subscript i) = the computed sample per stratum
n = sample
k = number of strata

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• 7.

### A type of probability sampling where the researcher randomly selects groups from an assemblage then considers the population for each selected group to be engaged in the study.

• A.

Simple random sampling

• B.

Systematic sampling

• C.

Stratified random sampling

• D.

Cluster sampling

D. Cluster sampling
Explanation
Cluster sampling is a type of probability sampling where the researcher randomly selects groups, or clusters, from a larger population. Each selected cluster represents a subset of the population, and all individuals within the selected clusters are considered to be part of the study. This method is useful when the population is large and dispersed, as it allows for a more efficient and cost-effective way of gathering data. By selecting clusters instead of individual participants, the researcher can reduce the time and resources required for data collection.

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• 8.

### During the course of his study, Felipe noted that the 514 patients were categorized based on their developmental stage. The following were listed: Adolescence 163, Young Adult 201, and Late Adult 150. Help Felipe in trying to compute for the sample per stratum using stratified random sampling with proportional allocation. This would give us:

• A.

• B.

• C.

• D.

Explanation
Prior to the computation of the sample per stratum, it is a need to compute for the required sample given the population using Yamane's formula where:
n = N / 1 + Ne (squared)
Having computed for the sample, the formula for stratified random sampling with a proportional allocation is:
n (subscript i) = [N (subscript i) / N] n
where n (subscript i) = the sample per stratum
N (subscript i) = the population per stratum
N = population
n = sample

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• 9.

### A type of non-probability sampling where the required sample and sample per stratum is determined and complied. However, it lacks randomization in the selection of the respondents for the study.

• A.

Convenience sampling

• B.

Judgment sampling

• C.

Snowball sampling

• D.

Quota sampling

D. Quota sampling
Explanation
Quota sampling is a type of non-probability sampling where the required sample and sample per stratum are determined and complied. It involves dividing the population into different strata based on certain characteristics, such as age, gender, or occupation, and then selecting individuals from each stratum until the quota for that stratum is met. However, unlike other sampling methods, quota sampling lacks randomization in the selection of respondents. This means that the sample may not be truly representative of the population, as the selection of individuals is based on convenience or judgment rather than random chance.

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• 10.

### Marice determines her respondents by asking people as to who would be most suited for her study. Through this, she is referred from one respondent to the other. What type of non-probability sampling has been utilized?

• A.

Convenience sampling

• B.

Snowball sampling

• C.

Judgment sampling

• D.

Quota sampling

B. Snowball sampling
Explanation
Snowball sampling has been utilized in this scenario. Snowball sampling is a non-probability sampling technique where initial participants are selected based on the researcher's judgment or convenience, and then they refer other potential participants who meet the criteria for the study. In this case, Marice determines her respondents by asking people who would be most suited for her study, and through this process, she is referred from one respondent to another. This method is often used when the target population is difficult to access or identify, and it allows for the recruitment of participants through social networks and referrals.

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• Current Version
• Mar 22, 2023
Quiz Edited by
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• Jan 19, 2013
Quiz Created by
Justin DCroix

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