Sampling

Model MCQ's Research Methodology

Sampling

1. Which of the following is the primary goal of sampling?

(A) To collect data from every individual in the population

(B) To estimate characteristics of the entire population

(D) To eliminate bias in data collection

(B) To estimate characteristics of the entire population

Explanation: Sampling allows researchers to collect data from a subset of the population, which is then used to make inferences about the entire population.

2. Which of the following sampling methods is used when every individual in the population has an equal chance of being selected?

(A) Stratified sampling

(B) Systematic sampling

(D) Cluster sampling

Explanation: Simple random sampling ensures that every individual has an equal chance of being selected, which is a key characteristic of this method.

3. In which of the following sampling methods are the population divided into distinct subgroups or strata?

(A) Simple random sampling

(B) Stratified sampling

(D) Convenience sampling

(B) Stratified sampling

Explanation: Stratified sampling involves dividing the population into subgroups (strata) and selecting samples from each of those strata.

4. What is the main characteristic of cluster sampling?

(A) Random selection of subgroups or clusters from a population

(B) Each individual is selected randomly from the entire population

(D) Participants are selected based on convenience

(A) Random selection of subgroups or clusters from a population

Explanation: In cluster sampling, the population is divided into groups or clusters, and then a random selection of these clusters is made.

5. Which of the following is a major disadvantage of convenience sampling?

(A) It is very time-consuming

(B) It provides a high level of precision

(D) It is complex and difficult to execute

Explanation: Convenience sampling involves selecting individuals based on ease of access, which may lead to selection bias and a non-representative sample.

6. Which of the following is the correct order of the sampling process?

(A) Define the population, choose the sample size, select the sampling method, collect data

(B) Define the population, collect data, select the sample size, choose the sampling method

(D) Select the sampling method, collect data, define the population, choose the sample size

(A) Define the population, choose the sample size, select the sampling method, collect data

Explanation: The sampling process begins with defining the population, followed by choosing the sample size, selecting the method, and then collecting the data.

7. Which of the following describes a systematic sampling method?

(A) Select every nth individual from a list

(B) Select individuals based on their geographic location

(D) Divide the population into strata and select from each subgroup

(A) Select every nth individual from a list

Explanation: Systematic sampling involves selecting every nth individual from a population list after choosing a random starting point.

8. What is the sampling frame?

(A) The exact population from which samples are drawn

(B) The list of all individuals in the population from which the sample is selected

(D) The procedure used for selecting the sample

(B) The list of all individuals in the population from which the sample is selected

Explanation: The sampling frame refers to the list of individuals or elements in the population from which a sample is drawn.

9. What is the main disadvantage of using simple random sampling?

(A) It may not provide an accurate representation of the population

(B) It cannot be generalized to the entire population

(D) It lacks flexibility

Explanation: While simple random sampling ensures an unbiased sample, it can be resource-intensive, particularly for large populations.

10. Which sampling method divides the population into subgroups and then selects samples from each subgroup?

(A) Stratified sampling

(B) Cluster sampling

(D) Convenience sampling

(A) Stratified sampling

Explanation: Stratified sampling divides the population into subgroups (strata) based on specific characteristics, and then samples are drawn from each of those strata.

11. In snowball sampling, how are participants selected?

(A) Individuals are selected randomly from the population

(B) Participants recruit other participants from their social network

(D) Participants are chosen from a pre-existing group

(B) Participants recruit other participants from their social network

Explanation: Snowball sampling is a non-probability sampling technique where existing participants refer new participants from their social network.

12. What is the main advantage of using stratified sampling?

(A) It provides a more accurate representation of the population

(B) It is faster and easier than other methods

(D) It works well for very large populations only

(A) It provides a more accurate representation of the population

Explanation: Stratified sampling ensures that all subgroups (strata) of the population are represented, making it more accurate and reliable compared to other methods.

13. What is the primary challenge in cluster sampling?

(A) Difficulty in defining clusters

(B) High cost and complexity

(D) Reduced generalizability

Explanation: Cluster sampling may lead to reduced generalizability, as clusters may not be fully representative of the entire population.

14. Which of the following is not a type of non-probability sampling?

(A) Convenience sampling

(B) Purposive sampling

(D) Snowball sampling

Explanation: Simple random sampling is a probability sampling method, whereas the other options are non-probability sampling methods.

15. What is quota sampling?

(A) A probability sampling method

(B) A method where certain characteristics of the population are deliberately over- or under-sampled

(D) A method that uses the most accessible participants

(B) A method where certain characteristics of the population are deliberately over- or under-sampled

Explanation: In quota sampling, the researcher ensures that specific subgroups within the population are represented by deliberately over- or under-sampling them.

16. What is the primary concern with convenience sampling?

(A) It requires a very large sample size

(B) It is too expensive to implement

(D) It is not representative of the population

Explanation: Convenience sampling is often biased because participants are chosen based on ease of access rather than being randomly selected from the population.

17. In systematic sampling, how do you determine the starting point?

(A) The starting point is chosen randomly from the list

(B) The starting point is the first individual in the list

(D) The starting point is determined by the researcher’s preference

(A) The starting point is chosen randomly from the list

Explanation: Systematic sampling requires choosing a random starting point in the list, and then every nth individual is selected.

18. Which type of sampling would you use if the population is already divided into groups, but you want to randomly sample entire groups rather than individuals?

(A) Stratified sampling

(B) Cluster sampling

(D) Simple random sampling

(B) Cluster sampling

Explanation: Cluster sampling is used when entire groups (clusters) are randomly selected from the population rather than selecting individuals within those groups.

19. Which of the following sampling methods provides the most precise estimates for large and heterogeneous populations?

(A) Simple random sampling

(B) Cluster sampling

(D) Stratified sampling

Explanation: Stratified sampling provides more precise estimates because it ensures all subgroups within the population are adequately represented.

20. In cluster sampling, what happens after the clusters are selected?

(A) A random sample is selected from each cluster

(B) Data is collected from a few individuals in each cluster

(D) Clusters are divided into smaller groups for more detailed sampling

Explanation: In cluster sampling, after selecting the clusters, the entire cluster is surveyed or sampled to represent the population.

21. What is the purpose of stratified sampling?

(A) To divide the population into strata based on similarities

(B) To reduce the overall sample size

(D) To avoid bias in data collection

(A) To divide the population into strata based on similarities

Explanation: Stratified sampling divides the population into distinct subgroups, or strata, and samples are drawn from each of these strata.

22. Which of the following is an example of non-probability sampling?

(A) Simple random sampling

(B) Systematic sampling

(D) Stratified sampling

Explanation: Convenience sampling is a non-probability sampling technique where participants are selected based on their ease of access to the researcher.

23. Which of the following statements is true about probability sampling methods?

(A) They offer equal chances of selection to every member of the population

(B) They involve selecting participants based on their availability

(D) They introduce a high level of bias

(A) They offer equal chances of selection to every member of the population

Explanation: Probability sampling ensures that every individual in the population has an equal chance of being selected, which helps to reduce bias.

24. In which sampling method do you choose every nth individual from a population list?

(A) Simple random sampling

(B) Systematic sampling

(D) Cluster sampling

(B) Systematic sampling

Explanation: Systematic sampling involves selecting every nth individual from a population list after choosing a random starting point.

25. What is the main disadvantage of stratified sampling?

(A) It is very costly

(B) It requires a random sample from each subgroup

(D) It requires a complete list of the population

Explanation: Stratified sampling requires a complete list of the population in order to divide it into subgroups (strata), which can be difficult or costly to obtain.

26. Which sampling technique involves selecting a sample from the population based on pre-defined criteria?

(A) Simple random sampling

(B) Systematic sampling

(D) Cluster sampling

Explanation: Purposive sampling involves selecting participants based on specific characteristics that the researcher is interested in studying.

27. What is the key feature of snowball sampling?

(A) Selection based on random chance

(B) Participants refer others from their social network

(D) It is only used for large populations

(B) Participants refer others from their social network

Explanation: Snowball sampling is a non-probability method where existing participants refer new participants from their social network, useful for studying hidden or hard-to-reach populations.

28. In which sampling method are clusters selected and the entire cluster is surveyed?

(A) Cluster sampling

(B) Stratified sampling

(D) Convenience sampling

(A) Cluster sampling

Explanation: In cluster sampling, the population is divided into clusters, and then entire clusters are selected and surveyed.

29. What is the main advantage of using simple random sampling?

(A) It is easy to implement

(B) It ensures all subgroups are represented

(D) It is the least expensive method

(A) It is easy to implement

Explanation: Simple random sampling is easy to implement because it involves randomly selecting individuals from the population, ensuring each individual has an equal chance of being chosen.

30. Which sampling method is best when the population is divided into distinct subgroups based on specific characteristics?

(A) Cluster sampling

(B) Stratified sampling

(D) Convenience sampling

(B) Stratified sampling

Explanation: Stratified sampling is ideal when the population has distinct subgroups or strata based on specific characteristics, and ensures that each subgroup is adequately represented in the sample.

31. Which of the following sampling techniques involves participants being selected from their social network?

(A) Snowball sampling

(B) Convenience sampling

(D) Simple random sampling

(A) Snowball sampling

Explanation: In snowball sampling, participants are selected through referrals from other participants, typically from a social network.

32. Which of the following is a key challenge in using quota sampling?

(A) It is difficult to implement

(B) It can introduce bias in selecting participants

(D) It provides a random sample

(B) It can introduce bias in selecting participants

Explanation: Quota sampling involves selecting participants to meet specific quotas based on certain characteristics, but it can introduce bias because the participants are not randomly selected.

33. Which of the following sampling methods is best suited for heterogeneous populations with clear subgroups?

(A) Stratified sampling

(B) Cluster sampling

(D) Convenience sampling

(A) Stratified sampling

Explanation: Stratified sampling is ideal for heterogeneous populations because it ensures that all subgroups (strata) are adequately represented in the sample.

34. What is an advantage of using convenience sampling?

(A) It provides a highly representative sample

(B) It is highly accurate

(D) It is quick and inexpensive

Explanation: Convenience sampling is easy and cost-effective to implement because it involves selecting participants who are readily available, but it can suffer from bias.

35. Which type of sampling is most likely to be used when a researcher has limited resources?

(A) Cluster sampling

(B) Stratified sampling

(D) Simple random sampling

Explanation: Convenience sampling is often used when resources are limited because it is cost-effective and quick, although it may introduce bias.

36. What is the main objective of using probability sampling methods?

(A) To allow the researcher to select participants based on convenience

(B) To ensure every member of the population has an equal chance of being selected

(D) To ensure that the sample is small and manageable

(B) To ensure every member of the population has an equal chance of being selected

Explanation: Probability sampling gives every individual in the population an equal chance of being selected, ensuring an unbiased and representative sample.

37. Which of the following is a disadvantage of systematic sampling?

(A) It is more expensive than other methods

(B) It requires a detailed understanding of the entire population

(D) It is not suitable for large populations

Explanation: Systematic sampling may lead to bias if the population list has a periodic pattern that aligns with the sampling interval, affecting the sample's representativeness.

38. In which of the following cases would cluster sampling be most appropriate?

(A) When the population is large and spread out geographically

(B) When a high degree of precision is needed

(D) When the researcher is working with small, well-defined groups

(A) When the population is large and spread out geographically

Explanation: Cluster sampling is ideal for large populations that are geographically spread out, as it reduces costs and effort by sampling entire clusters rather than individuals.

39. Which of the following is true about the sampling frame?

(A) It refers to the entire population being studied

(B) It is a list of all individuals or elements in the population from which a sample is drawn

(D) It refers to the final selected sample

(B) It is a list of all individuals or elements in the population from which a sample is drawn

Explanation: The sampling frame is the complete list of individuals or elements that are available to be included in the sample, from which the researcher selects the participants.

40. Which sampling method is most appropriate when subgroups of the population differ in key characteristics that are important for the research?

(A) Stratified sampling

(B) Simple random sampling

(D) Cluster sampling

(A) Stratified sampling

Explanation: Stratified sampling is best when the population contains subgroups with different characteristics that are important to the research, ensuring each subgroup is adequately represented.

41. Which sampling method is used when the population is divided into subgroups, and then some entire subgroups are selected randomly?

(A) Stratified sampling

(B) Systematic sampling

(D) Convenience sampling

Explanation: In cluster sampling, the population is divided into clusters, and then a random selection of entire clusters is made for data collection.

42. Which of the following statements is true about convenience sampling?

(A) It provides a highly representative sample

(B) It is random and unbiased

(D) It is the best method for large, heterogeneous populations

Explanation: Convenience sampling selects participants based on their availability, which can lead to bias and may not provide a representative sample of the population.

43. Which of the following is an example of probability sampling?

(A) Convenience sampling

(B) Purposive sampling

(D) Simple random sampling

Explanation: Simple random sampling is a probability sampling method where every individual has an equal chance of being selected from the population.

44. What is the key characteristic of purposive sampling?

(A) Random selection of participants

(B) Participants are selected based on specific characteristics relevant to the study

(D) It involves the use of social networks for participant selection

(B) Participants are selected based on specific characteristics relevant to the study

Explanation: In purposive sampling, participants are selected deliberately based on characteristics that align with the research objectives.

45. What is the purpose of sampling error?

(A) To measure the bias introduced by non-random selection

(B) To quantify the difference between the sample and the population parameter

(D) To ensure that the sample is accurate

(B) To quantify the difference between the sample and the population parameter

Explanation: Sampling error is the difference between the sample's estimate and the true population value, and it occurs due to random chance during sampling.

46. Which of the following methods is best for ensuring a completely random sample?

(A) Systematic sampling

(B) Stratified sampling

(D) Cluster sampling

Explanation: Simple random sampling ensures complete randomness by giving every member of the population an equal chance of being selected.

47. What does non-probability sampling lack that probability sampling has?

(A) Random selection

(B) A sample frame

(D) All of the above

(A) Random selection

Explanation: Non-probability sampling lacks the element of random selection, which means that not every member of the population has a known chance of being selected.

48. What is an advantage of using systematic sampling over simple random sampling?

(A) It ensures more randomization

(B) It is easier to implement and faster

(D) It requires a larger sample size

(B) It is easier to implement and faster

Explanation: Systematic sampling is quicker and simpler to implement compared to simple random sampling, especially when dealing with large populations.

49. What is the main goal of using stratified sampling?

(A) To reduce the time spent on data collection

(B) To avoid random errors in sampling

(D) To ensure that all subgroups of the population are represented proportionally

Explanation: Stratified sampling divides the population into subgroups (strata) and ensures that each subgroup is proportionally represented in the sample, improving the accuracy of the results.

50. What is one disadvantage of using cluster sampling?

(A) It is very time-consuming

(B) The entire population must be known

(D) It requires large sample sizes

Explanation: Cluster sampling may lead to biased results if the clusters are not heterogeneous enough, meaning that the selected clusters may not represent the diversity of the whole population.

51. Which of the following is a benefit of convenience sampling?

(A) It provides a highly accurate sample of the population

(B) It is cost-effective and easy to implement

(D) It ensures random selection

(B) It is cost-effective and easy to implement

Explanation: Convenience sampling is often used because it is inexpensive and quick, especially when access to the population is limited or hard to reach.

52. Which of the following is an example of a non-probability sampling method?

(A) Simple random sampling

(B) Cluster sampling

(D) Judgmental sampling

Explanation: Judgmental sampling (also known as purposive sampling) is a non-probability sampling technique where the researcher selects individuals based on specific characteristics or judgment rather than random selection.

53. Which of the following is a potential problem when using systematic sampling?

(A) It is too complex to execute

(B) It may introduce bias if the population has a cyclical pattern that matches the sampling interval

(D) It is time-consuming

(B) It may introduce bias if the population has a cyclical pattern that matches the sampling interval

Explanation: Systematic sampling may introduce bias if there is a periodic or cyclical pattern in the population that coincides with the sampling interval, leading to unrepresentative samples.

54. Which sampling technique is often used when the population is difficult to access or hidden?

(A) Snowball sampling

(B) Simple random sampling

(D) Cluster sampling

(A) Snowball sampling

Explanation: Snowball sampling is used when the population is difficult to access or hidden. It works by asking initial participants to refer others to join the study, creating a "snowball" effect.

55. What does the term "sampling bias" refer to?

(A) The selection of a sample that accurately represents the population

(B) The selection of participants based on random chance

(D) A bias introduced by statistical analysis errors

Explanation: Sampling bias occurs when the sample selected does not accurately represent the population, often due to non-random selection or under-representation of certain subgroups.

56. Which type of sampling is often used for qualitative research where specific individuals are selected for their expertise or experience?

(A) Snowball sampling

(B) Purposive sampling

(D) Stratified sampling

(B) Purposive sampling

Explanation: Purposive sampling is used in qualitative research to select individuals based on their specific characteristics or expertise relevant to the research question.

57. What is the purpose of a sample frame?

(A) To define the total population

(B) To select the best method for data analysis

(D) To list all possible units in the population from which a sample can be drawn

Explanation: A sample frame is the list of all individuals or elements from which the sample is drawn. It is essential for ensuring that the sample is representative of the population.

58. Which sampling method requires the researcher to choose every nth individual from a population list?

(A) Stratified sampling

(B) Systematic sampling

(D) Convenience sampling

(B) Systematic sampling

Explanation: In systematic sampling, the researcher selects every nth individual from a population list after choosing a random starting point.

59. Which of the following is a characteristic of probability sampling methods?

(A) The researcher selects participants based on convenience

(B) It does not require a sample frame

(D) Every member of the population has a known and non-zero chance of being selected

Explanation: Probability sampling methods ensure that each individual in the population has a known and equal chance of being selected, reducing the risk of bias.

60. Which of the following sampling methods involves dividing the population into mutually exclusive groups and selecting a random sample from each group?

(A) Stratified sampling

(B) Simple random sampling

(D) Cluster sampling

(A) Stratified sampling

Explanation: Stratified sampling involves dividing the population into mutually exclusive groups (strata) and selecting a random sample from each group to ensure representation of all subgroups.

61. Which of the following is a key advantage of probability sampling over non-probability sampling?

(A) It eliminates the need for a sample frame

(B) It ensures a more representative sample

(D) It is more flexible in terms of sample selection

(B) It ensures a more representative sample

Explanation: Probability sampling methods provide equal chances for every individual to be selected, making the sample more likely to represent the entire population accurately.

62. What is the main feature of quota sampling?

(A) Random selection from the population

(B) Ensuring specific subgroups are represented in the sample

(D) Using a simple random method to choose participants

(B) Ensuring specific subgroups are represented in the sample

Explanation: In quota sampling, the researcher deliberately over- or under-samples certain subgroups to ensure they are adequately represented in the final sample.

63. Which of the following is a common problem with using judgmental (purposive) sampling?

(A) It ensures that every individual in the population is represented

(B) It can introduce researcher bias

(D) It requires a large sample size

(B) It can introduce researcher bias

Explanation: Judgmental or purposive sampling relies on the researcher’s judgment to select participants, which can introduce bias if the researcher’s criteria are not objective.

64. What does the term "sampling error" refer to?

(A) The difference between the sample mean and the population mean

(B) The error made during data collection

(D) The random error that occurs in the data analysis process

(A) The difference between the sample mean and the population mean

Explanation: Sampling error refers to the discrepancy between the sample mean and the true population mean, which is expected in any sample-based research.

65. Which sampling method is most appropriate when the population is divided into natural or pre-existing groups?

(A) Stratified sampling

(B) Systematic sampling

(D) Simple random sampling

Explanation: Cluster sampling is ideal when the population is naturally divided into groups (clusters), and entire clusters are selected to represent the population.

66. Which of the following is true about simple random sampling?

(A) It requires a stratified list of the population

(B) It guarantees that every individual in the population has an equal chance of selection

(D) It requires choosing every nth individual from a population

(B) It guarantees that every individual in the population has an equal chance of selection

Explanation: Simple random sampling ensures that every individual has an equal and independent chance of being selected, minimizing bias.

67. In which of the following situations would cluster sampling be most effective?

(A) When there is a clear hierarchy within the population

(B) When the population is homogenous and well-mixed

(D) When there is a need for high precision in estimates

Explanation: Cluster sampling is effective when groups or clusters of individuals are accessible, making it easier to collect data from these groups rather than from the entire population.

68. What is a key feature of convenience sampling?

(A) It is a type of probability sampling

(B) It selects participants based on random selection

(D) It ensures equal representation of all subgroups

Explanation: Convenience sampling selects individuals who are easiest to reach or who are conveniently available to the researcher, leading to a non-random sample.

69. Which sampling method is most useful when researchers want to ensure that certain subgroups are proportionately represented in the sample?

(A) Simple random sampling

(B) Systematic sampling

(D) Cluster sampling

Explanation: Stratified sampling ensures that subgroups (strata) of the population are represented proportionally, improving the accuracy of the sample’s representation.

70. Which of the following is a limitation of snowball sampling?

(A) It can lead to biased results due to the researcher’s selection

(B) It is difficult to analyze the data

(D) It may not provide a diverse sample

Explanation: Snowball sampling relies on participants referring others, which can lead to a sample that lacks diversity or is limited to a specific social network.

71. In systematic sampling, the sampling interval is:

(A) The number of individuals to select

(B) The distance between each selected individual

(D) The number of clusters to select

(B) The distance between each selected individual

Explanation: In systematic sampling, the sampling interval is the fixed number (n) used to select every nth individual from the population list.

72. Which of the following is a characteristic of non-probability sampling methods?

(A) Every member of the population has an equal chance of being selected

(B) The researcher selects participants based on subjective judgment

(D) It eliminates sampling bias

(B) The researcher selects participants based on subjective judgment

Explanation: Non-probability sampling methods rely on the researcher’s judgment to select participants, making them prone to selection bias.

73. Which type of sampling would you use if you wanted to make sure that the sample accurately reflects the proportion of certain characteristics in the population?

(A) Simple random sampling

(B) Stratified sampling

(D) Cluster sampling

(B) Stratified sampling

Explanation: Stratified sampling divides the population into subgroups (strata) based on certain characteristics, ensuring that each subgroup is adequately represented in the sample. This helps maintain the proportion of specific characteristics in the sample similar to that in the population.

74. In what scenario would you use quota sampling?

(A) When random selection is impractical

(B) When you want to ensure a random sample

(D) When it is difficult to get a complete list of the population

Explanation: Quota sampling is used when researchers want to ensure specific subgroups (segments) are represented proportionally in the sample.

75. Which type of sampling is most likely to produce a biased sample?

(A) Simple random sampling

(B) Systematic sampling

(D) Stratified sampling

Explanation: Convenience sampling is prone to bias because it selects individuals who are easiest to access, potentially excluding certain groups from the sample.

76. What is a key disadvantage of stratified sampling?

(A) It can lead to high costs and logistical challenges

(B) It is not suitable for heterogeneous populations

(D) It may result in bias in sample selection

(A) It can lead to high costs and logistical challenges

Explanation: Stratified sampling can be more complex and costly because it requires identifying and organizing subgroups within the population.

77. Which sampling method would be appropriate for surveying a large, geographically dispersed population?

(A) Snowball sampling

(B) Stratified sampling

(D) Convenience sampling

Explanation: Cluster sampling is ideal for large, dispersed populations because it involves selecting entire clusters (groups) rather than individual members, making the survey process more efficient.

78. What is the sampling technique used when the population is divided into homogeneous groups and random samples are taken from each group?

(A) Simple random sampling

(B) Stratified sampling

(D) Cluster sampling

(B) Stratified sampling

Explanation: In stratified sampling, the population is divided into homogeneous subgroups (strata), and random samples are selected from each subgroup to ensure diversity in the sample.

79. In which type of sampling are participants selected from different clusters based on random selection?

(A) Stratified sampling

(B) Systematic sampling

(D) Convenience sampling

Explanation: Cluster sampling involves selecting entire groups (clusters) at random and then surveying individuals within those clusters. This method is useful when the population is large and spread over a wide geographic area, as it reduces cost and time associated with data collection.

80. Which sampling technique is most appropriate when the population is large, spread out geographically, and difficult to access in its entirety?

(A) Stratified sampling

(B) Systematic sampling

(D) Convenience sampling

Explanation: Cluster sampling is useful when the population is geographically dispersed and difficult to access. In this technique, the population is divided into clusters, and a random sample of these clusters is selected for further study.

81. What is the primary disadvantage of cluster sampling?

(A) It is difficult to implement

(B) It may not be as precise as other methods

(D) It requires a high level of expertise

(B) It may not be as precise as other methods

Explanation: Cluster sampling can result in less precise estimates than other methods, especially if the clusters are not homogeneous and differ widely from each other.

82. In what situation would you use systematic sampling over simple random sampling?

(A) When the population is small

(B) When the population list is already in a random order

(D) When the population list is organized in some logical order

Explanation: Systematic sampling is preferred when the population list is ordered in some way. You select every nth individual starting from a random point, making it easier to implement than simple random sampling in such cases.

83. Which of the following is a characteristic of probability sampling?

(A) All units in the population have an equal chance of being selected

(B) Participants are selected based on their convenience

(D) There is no randomness in the selection process

(A) All units in the population have an equal chance of being selected

Explanation: In probability sampling, each unit in the population has a known and equal chance of being selected, which helps in achieving unbiased and representative samples.

84. Which of the following is true for convenience sampling?

(A) It is a probability sampling method

(B) It involves selecting participants who are easiest to access

(D) It is more accurate than other sampling methods

(B) It involves selecting participants who are easiest to access

Explanation: Convenience sampling involves selecting participants based on their availability and ease of access, which can introduce bias and make the sample unrepresentative of the population.

85. What is the goal of random sampling?

(A) To ensure that every participant has an equal chance of being selected

(B) To select participants based on their characteristics

(D) To reduce the sample size

(A) To ensure that every participant has an equal chance of being selected

Explanation: Random sampling ensures that each member of the population has an equal chance of being selected, which helps reduce bias and makes the sample representative of the population.

86. Which type of sampling method is best for ensuring that each subgroup of a population is properly represented?

(A) Simple random sampling

(B) Stratified sampling

(D) Cluster sampling

(B) Stratified sampling

Explanation: Stratified sampling divides the population into subgroups (strata) based on characteristics and then samples from each subgroup. This ensures that each subgroup is well-represented in the sample.

87. In which situation would snowball sampling be used?

(A) When the population is well-defined and easily accessible

(B) When the sample needs to be representative of the entire population

(D) When researching a population that is difficult to access, such as a hidden population

Explanation: Snowball sampling is often used for hard-to-reach or hidden populations. Initial participants refer others, and the sample size grows like a snowball.

88. What is the main advantage of using probability sampling over non-probability sampling?

(A) Probability sampling reduces the likelihood of bias

(B) Probability sampling is quicker

(D) Probability sampling always gives more accurate results

(A) Probability sampling reduces the likelihood of bias

Explanation: Probability sampling methods reduce the likelihood of bias because every unit in the population has an equal chance of being selected, leading to more representative and generalizable samples.

89. Which of the following is an example of a non-probability sampling method?

(A) Simple random sampling

(B) Stratified sampling

(D) Convenience sampling

Explanation: Convenience sampling is a non-probability sampling method where participants are selected based on their ease of access, rather than through random selection.

90. What does a sampling frame refer to?

(A) A list of all elements or units in the population

(B) A group of participants selected for the study

(D) A random number generator used to select the sample

(A) A list of all elements or units in the population

Explanation: The sampling frame is the actual list or representation of the population from which the sample is drawn. It is crucial for ensuring that all elements of the population have a chance of being included.

91. Which of the following is a key difference between probability and non-probability sampling methods?

(A) Probability sampling is faster than non-probability sampling

(B) In probability sampling, every member of the population has a known and non-zero chance of being selected

(D) Probability sampling does not require a sampling frame

(B) In probability sampling, every member of the population has a known and non-zero chance of being selected

Explanation: Probability sampling ensures that every member of the population has an equal or known chance of being selected, which helps in making generalizations. Non-probability sampling methods do not guarantee equal chances of selection.

92. What is the main goal of using a stratified sampling method?

(A) To ensure that different subgroups of the population are properly represented in the sample

(B) To select participants randomly from the entire population

(D) To reduce the overall sample size

(A) To ensure that different subgroups of the population are properly represented in the sample

Explanation: Stratified sampling divides the population into distinct subgroups (strata), ensuring that all subgroups are proportionally represented in the sample.

93. Which of the following is NOT a characteristic of a well-designed sampling frame?

(A) It accurately represents the entire population

(B) It is updated regularly

(D) It should cover all potential participants in the population

Explanation: A good sampling frame should include all eligible individuals in the population to ensure that the sample is representative. Excluding eligible individuals would lead to bias.

94. In which of the following situations would convenience sampling be appropriate?

(A) When accuracy is the top priority

(B) When the researcher needs a quick and easy sample

(D) When the research requires a representative sample

(B) When the researcher needs a quick and easy sample

Explanation: Convenience sampling is appropriate when the researcher needs to gather data quickly and easily, although it may introduce bias and not be representative of the entire population.

95. Which sampling method would you use if you wanted to collect data from every 10th person on a list of participants?

(A) Simple random sampling

(B) Systematic sampling

(D) Cluster sampling

(B) Systematic sampling

Explanation: Systematic sampling involves selecting every nth individual from a population list, such as every 10th person, after choosing a random starting point.

96. What is the primary advantage of using a random number generator in the selection process of simple random sampling?

(A) It reduces the sample size

(B) It ensures that only specific types of individuals are selected

(D) It ensures that every individual has an equal chance of being selected

Explanation: Using a random number generator ensures that the selection process is random and unbiased, giving every individual in the population an equal chance of being selected.

97. Which sampling method is best suited for studying a very specific, hard-to-reach group of people?

(A) Simple random sampling

(B) Stratified sampling

(D) Systematic sampling

Explanation: Snowball sampling is best suited for studying hard-to-reach or hidden populations, as initial participants recruit other participants from their social network, gradually expanding the sample.

98. In a cluster sampling design, what is typically the next step after clusters have been selected?

(A) A sample is selected from each individual in the cluster

(B) A random sample is chosen from the population

(D) The clusters are divided into smaller subgroups for further sampling

Explanation: In cluster sampling, after selecting clusters, entire clusters are often surveyed or sampled to represent the population. This method is often used for large and dispersed populations.

99. Which of the following sampling methods involves the selection of participants from pre-existing groups or clusters?

(A) Cluster sampling

(B) Convenience sampling

(D) Systematic sampling

(A) Cluster sampling

Explanation: Cluster sampling involves dividing the population into groups or clusters, and then selecting entire clusters for study. It is often used when individuals in the population are not easily accessible.

100. Which type of sampling would be best suited for an online survey where participants are selected based on who volunteers?

(A) Simple random sampling

(B) Convenience sampling

(D) Snowball sampling

(B) Convenience sampling

Explanation: Convenience sampling is often used in online surveys where participants are selected based on their availability or willingness to volunteer, although this method can introduce bias.

Sampling

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