Sampling Design Techniques Quiz

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| By Justin DCroix

Justin DCroix

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1/10 Questions

A sampling technique is used in Qualitative research wherein the researcher chooses individuals who are easily accessible to become respondents for the study.
- Judgment Sampling
- Convenience Sampling
- Snowball Sampling
- Quota Sampling

About This Quiz

Are you ready to test your knowledge of research methods? This Sampling Design Techniques Quiz is perfect for students, researchers, and anyone interested in understanding the different methods used in sampling. This quiz covers all the essential techniques used in research design.

Each question is designed to challenge your understanding of how different sampling methods work, their advantages and See moredisadvantages, and their applications in various research scenarios. By taking this quiz, you can assess your grasp of key concepts and improve your knowledge of how to choose the most appropriate sampling method for a study. Take the quiz now and see how well you know the strategies behind sampling in research!

$Sampling Design Techniques Quiz - Quiz$

2.

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?
- Convenience sampling
- Snowball sampling
- Judgment sampling
- Quota sampling
Correct Answer

A. 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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3.

Which among the following formulas is relevant towards systematic random sampling?
- K = N / n
- N = N / k
- N = (Ni / N) (n)
- K = (N)(N) / 2n
Correct Answer

A. K = N / n

Explanation

Systematic random sampling is a method where elements are selected from an ordered population at regular intervals, known as the sampling interval. The formula k = N / n is used to calculate this interval, where:
k is the sampling interval,
N is the total population size,
n is the desired sample size.
By dividing the total population (N) by the desired sample size (n), the researcher determines how frequently (every k-th element) to select an individual from the list. For example, if there are 1,000 individuals in a population (N) and a researcher wants a sample of 100 (n), then the sampling interval (k) would be 10. This means every 10th person from a randomly ordered list would be selected for the sample, ensuring a systematic but still random selection of participants across the entire population. This technique helps in achieving a representative sample while maintaining simplicity and cost-efficiency in data collection.

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5
4.

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.
- Convenience sampling
- Judgment sampling
- Snowball sampling
- Quota sampling
Correct Answer

A. 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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14
5.

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?
- Systematic random sampling
- Stratified random sampling with equal allocation
- Stratified random sampling with proportional allocation
- Cluster sampling
Correct Answer

A. 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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7
6.

What is the main difference between probability and non-probability sampling?
- Probability sampling involves random selection, giving every element a known chance of being selected.
- Non-probability sampling is often used when it is impossible to conduct probability sampling.
- Probability sampling is more suitable for qualitative research, while non-probability sampling is for quantitative research.
- Non-probability sampling always provides more accurate results than probability sampling.
Correct Answer

A. Probability sampling is more suitable for qualitative research, while non-probability sampling is for quantitative research.

Explanation

The main difference between probability and non-probability sampling lies in the selection method. Probability sampling uses random selection, which gives every element in the population a known and equal chance of being included in the sample. This allows for the results to be generalizable to the population. On the other hand, non-probability sampling does not involve random selection, and the elements are selected based on the researcher's judgment, convenience, or other criteria. This makes non-probability sampling less generalizable but useful in exploratory research where probability sampling is not feasible.

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7
7.

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:
- Convenience sampling
- Judgment sampling
- Snowball sampling
- Quota sampling
Correct Answer

A. 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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15
8.

Michael wanted to have an equal allocation of units per sample for each stratum in a population of 352. The following are the subpopulations for each stratum: Chinese 125, Japanese 84, Filipino 94, and Korean 49. How many samples for each stratum would be needed if equal allocation is used?
- 37
- 88
- 57
- 67
Correct Answer

A. 88

Explanation

When using equal allocation in stratified random sampling, the sample size is the same for each stratum regardless of the size of the subpopulation. In this scenario, Michael wants an equal number of samples from each of the four subpopulations. Given the total population of 352, dividing it by 4 strata results in 88 samples per stratum. This approach ensures that each stratum is equally represented, which is useful in certain studies where equal representation is more important than proportional representation.

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11
9.

During the course of his study, Felipe noted that the 514 patients were categorized based on their developmental stage: Adolescence 163, Young Adult 201, and Late Adult 150. Help Felipe compute the sample per stratum using stratified random sampling with proportional allocation. Which of the following is the correct allocation?
- Adolescent 65, Young Adult 93, Late Adult 66
- Adolescent 71, Young Adult 88, Late Adult 66
- Adolescent 71, Young Adult 80, Late Adult 74
- Adolescent 62, Young Adult 93, Late Adult 78
Correct Answer

A. Adolescent 71, Young Adult 88, Late Adult 66

Explanation

To determine the sample size for each stratum:
Calculate the proportion of each stratum:
Adolescents: 163 out of 514
Young Adults: 201 out of 514
Late Adults: 150 out of 514
Determine the overall desired sample size:
For this example, let's assume the desired sample size is 225 (this could be calculated using a formula like Yamane's formula, but for simplicity, we are using 225).
Calculate the sample size for each stratum:
Adolescents: (163 / 514) * 225 = 71
Young Adults: (201 / 514) * 225 = 88
Late Adults: (150 / 514) * 225 = 66
These calculations result in the sample sizes being proportional to the population sizes: 71 Adolescents, 88 Young Adults, and 66 Late Adults. This ensures that the sample reflects the population distribution accurately, giving us the correct allocation.

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4
10.

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.
- Simple random sampling
- Systematic sampling
- Stratified random sampling
- Cluster sampling
Correct Answer

A. 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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Sep 09, 2024

Quiz Edited by
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Jan 19, 2013

Quiz Created by
Justin DCroix

Sampling Design Techniques Quiz

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

Quiz Preview

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?

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

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.

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?

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

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:

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

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.