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Sampling Quiz 10 (10 MCQs)

This set of multiple-choice questions evaluates understanding of population, sample, and various sampling methods including random sampling, stratified sampling, and convenience sampling. It assesses the ability to identify population vs. sample, understand survey methodology, and recognize unbiased sampling techniques. Concepts such as nonresponse error, selection bias, and representation are also covered.

Quiz Instructions

Select an option to see the correct answer instantly.

1. What is criterion-based sampling in qualitative research?

Correct Answer: Correct answer is: (A) Participants must meet specific criteria relevant to the study.

Exam Relevance: Qualitative Research Methods, Social Science Research, Psychology Research Methods

Difficulty: Moderate

Concept notes: Criterion-based sampling in qualitative research involves selecting participants based on specific criteria that are relevant to the study's objectives.

Common Mistakes: A common misunderstanding is that criterion-based sampling is the same as random sampling, which is not true. Random sampling involves selecting participants randomly, whereas criterion-based sampling involves selecting participants who meet specific criteria.

Explanations: Criterion-based sampling is a method used in qualitative research where participants are chosen based on specific criteria that are pertinent to the research objectives. This ensures that the sample is representative of the population of interest and that the data collected is relevant to the research questions.

Option Analysis:

Option A: Correct. Participants must meet specific criteria relevant to the study.
Option B: Incorrect. Random selection of participants is not criterion-based sampling.
Option C: Incorrect. Numerical data collection is not related to criterion-based sampling.
Option D: Incorrect. Generalization of findings is not a characteristic of criterion-based sampling.

2. Mr. Roberts is forming a faculty advisory committee. He decides to randomly choose 2 teachers from each of the core content subjects. This is an example of

Correct Answer: Correct answer is: (D) Stratified sampling.

Exam Relevance: AP Statistics, IB Mathematics, GRE, GMAT

Difficulty: Moderate

Concept notes: Stratified sampling involves dividing the population into distinct subgroups (strata) and then randomly selecting samples from each subgroup. This ensures that each subgroup is represented in the sample.

Common Mistakes: A common misunderstanding is confusing stratified sampling with simple random sampling, where every individual in the population has an equal chance of being selected without any subgroup division.

Explanations: In this scenario, Mr. Roberts is forming a faculty advisory committee by randomly choosing 2 teachers from each of the core content subjects. This method ensures that each subject (stratum) is represented in the sample, which is the essence of stratified sampling.

Option Analysis:

Option A: Simple random sampling involves selecting individuals from the entire population without any subgroup division, which does not apply here.
Option B: Systematic sampling involves selecting individuals at regular intervals from a list, which is not the method used here.
Option C: Cluster sampling involves dividing the population into clusters and randomly selecting entire clusters, which is not the method used here.
Option D: Stratified sampling involves dividing the population into strata and randomly selecting from each stratum, which matches the method used here.

Mnemonic: S-S-S: Stratified Sampling Selects Subgroups

3. A sample is a segment of the population selected for marketing research to represent the population as a whole

Correct Answer: Correct answer is: (A) TRUE.

Exam Relevance: AP Statistics, GRE, GMAT, Marketing Research Exams

Difficulty: Easy

Concept notes: A sample is a subset of the population that is selected for research to represent the entire population.

Common Mistakes: A common misunderstanding is that a sample must be identical to the population, which is not true. A sample should be representative, not identical.

Explanations: A sample is a segment of the population selected for marketing research to represent the population as a whole. This is a fundamental concept in sampling, where the goal is to make inferences about the population based on the characteristics of the sample. The sample should be representative of the population to ensure accurate and reliable results.

Option Analysis:

Option A: This option is correct because a sample is indeed a segment of the population selected to represent the entire population.
Option B: This option is incorrect because it contradicts the definition and purpose of a sample in research.

4. Kim surveys 100 moviegoers that entered the movie theater in the first hour. What type of sampling method is this?

Correct Answer: Correct answer is: (B) Convenience.

Exam Relevance: AP Statistics, IB Mathematics, GRE, GMAT

Difficulty: Easy

Concept notes: Convenience sampling involves selecting individuals who are easiest to reach or most readily available. In this case, Kim surveys moviegoers who entered the theater in the first hour, which is a convenient group to access.

Common Mistakes: A common mistake is to confuse convenience sampling with random sampling. Random sampling requires each individual in the population to have an equal chance of being selected, which is not the case here.

Explanations: Convenience sampling is used when the sample is selected based on ease of access. Kim surveys 100 moviegoers who entered the theater in the first hour, which is a convenient group to reach. This method does not ensure that the sample is representative of the entire population of moviegoers, but it is the easiest way to gather data in this scenario.

Option Analysis:

Option A: Random sampling requires each individual in the population to have an equal chance of being selected, which is not the case here.
Option B: Convenience sampling involves selecting individuals who are easiest to reach or most readily available, which fits the scenario described.
Option C: Biased sampling occurs when the sample is not representative of the population, but this is not the defining characteristic of the method used here.
Option D: Self-selected sampling occurs when individuals volunteer to participate, which is not the case here.

5. Devon is studying the relationship between the rate of teen pregnancies in U.S. high school students and the availability of contraceptives. She selects a sample composed of equal numbers of first-year, sophomore, junior, and senior women from a local high school. Devon's sample is

Correct Answer: Correct answer is: (C) Representative.

Exam Relevance: AP Statistics, GRE, MCAT

Difficulty: Moderate

Concept notes: A representative sample is one that accurately reflects the characteristics of the population being studied. In this case, Devon's sample includes equal numbers of first-year, sophomore, junior, and senior women, which ensures that the sample reflects the distribution of these groups in the high school population.

Common Mistakes: A common misunderstanding is that a random sample is the same as a representative sample. While a random sample can be representative, it is not guaranteed to be so. A representative sample specifically aims to reflect the population's characteristics.

Explanations: Devon's sample is representative because it includes equal numbers of first-year, sophomore, junior, and senior women. This ensures that the sample reflects the distribution of these groups in the high school population, making it a representative sample.

Option Analysis:

Option A: The sample is not biased because it includes equal numbers of students from each year, which avoids over-representation or under-representation of any particular group.
Option B: The sample is not necessarily random, as random sampling involves selecting individuals from the population in a way that each individual has an equal chance of being selected. Devon's sample is stratified, ensuring equal representation from each year.
Option C: The sample is representative because it includes equal numbers of students from each year, reflecting the population's distribution.
Option D: The sample may not be generalizable to all high schools, as it is specific to one local high school and may not reflect the broader population of U.S. high school students.

6. Alaa is going to send out a survey. To ensure that a sample represents a target population, Alaa selects

Correct Answer: Correct answer is: (A) People at random from the target population.

Exam Relevance: AP Statistics, GRE, GMAT, SAT

Difficulty: Moderate

Concept notes: To ensure a sample represents the target population accurately, it is essential to select individuals randomly from the entire population. This method helps to avoid bias and ensures that every individual has an equal chance of being included in the sample.

Common Mistakes: A common misunderstanding is that selecting a large number of people from one subgroup or a slightly larger percentage from certain subgroups will ensure a representative sample. However, this can introduce bias and skew the results.

Explanations: Random selection from the target population ensures that the sample is representative of the entire population. This method minimizes selection bias and increases the likelihood that the sample accurately reflects the characteristics of the target population. By choosing individuals at random, each member of the population has an equal chance of being included, which is crucial for obtaining unbiased results.

Option Analysis:

Option A: This is the correct approach for ensuring a representative sample. Random selection from the target population minimizes bias and ensures that the sample reflects the population accurately.
Option B: Selecting a large number of people from one subgroup can introduce bias and does not ensure a representative sample of the entire population.
Option C: Selecting a slightly larger percentage of people from certain subgroups can also introduce bias and does not ensure a representative sample of the entire population.
Option D: This option is incorrect because not all of the above methods ensure a representative sample. Only random selection from the target population is the correct approach.

Mnemonic: Random = Representative

7. Random sampling of subjects is not possible in survey research design

Correct Answer: Correct answer is: (B) False.

Exam Relevance: AP Statistics, GRE, GMAT, MCAT

Difficulty: Moderate

Concept notes: Random sampling is a method used in survey research to ensure that every member of the population has an equal chance of being selected. This method is often used to obtain a representative sample of the population.

Common Mistakes: A common misunderstanding is that random sampling is not feasible in survey research, which is incorrect. Random sampling is indeed possible and is a standard practice in survey research to ensure unbiased results.

Explanations: Random sampling is a fundamental technique in survey research. It involves selecting subjects from a population in such a way that each subject has an equal probability of being chosen. This method helps to ensure that the sample is representative of the entire population, reducing bias and improving the reliability of the survey results. Therefore, the statement that random sampling of subjects is not possible in survey research design is false.

Option Analysis:

Option A: This option suggests that random sampling is not possible in survey research, which is incorrect.
Option B: This option correctly states that random sampling is possible in survey research.

8. The textbook of Johnson and Christensen recommended that you include the entire population in your research study when the population is 100 or less.

Correct Answer: Correct answer is: (A) True.

Exam Relevance: AP Statistics, GRE, GMAT, Research Methods Exams

Difficulty: Easy

Concept notes: When the population size is small, such as 100 or less, it is often recommended to include the entire population in the research study to ensure comprehensive and accurate data.

Common Mistakes: A common misunderstanding is that sampling is always necessary, even for small populations. However, for very small populations, including the entire population can provide more precise results.

Explanations: In sampling theory, when the population size is small (100 or less), it is often more practical and accurate to include the entire population in the study rather than using a sample. This ensures that all members of the population are accounted for, providing a complete and accurate representation of the data.

Option Analysis:

Option A: This option is correct because including the entire population in the study when the population is 100 or less is recommended to ensure comprehensive and accurate data.
Option B: This option is incorrect because it contradicts the recommendation to include the entire population in the study when the population is small.

9. ..... is the entire group of objects or individuals considered for a survey.

Correct Answer: Correct answer is: (B) Population.

Exam Relevance: AP Statistics, GRE, GMAT, SAT

Difficulty: Easy

Concept notes: In sampling, the population is the entire group of objects or individuals considered for a survey.

Common Mistakes: A common misunderstanding is confusing the population with a sample, which is only a subset of the population.

Explanations: The population is the complete set of elements or items having common characteristics that are subject to analysis. In the context of a survey, the population includes all the individuals or objects that are of interest for the study. The term "sample" refers to a subset of the population, not the entire group.

Option Analysis:

Option A: A sample is a subset of the population, not the entire group.
Option B: The population is the entire group of objects or individuals considered for a survey.
Option C: A random sample is a subset of the population selected randomly, not the entire group.
Option D: Quartiles are divisions of data into four equal parts, not the entire group.

10. This category of error occurs when a sample does not represent the target population. Nonresponse error (the respondents differ from the sample) is an example.

Correct Answer: Correct answer is: (A) Sampling Error.

Exam Relevance: AP Statistics, GRE, GMAT, MCAT

Difficulty: Moderate

Concept notes: Sampling error occurs when a sample does not accurately represent the target population. This can happen due to various reasons, including nonresponse error, where the respondents differ from the sample.

Common Mistakes: A common misunderstanding is that sampling error only occurs due to random chance. However, it can also occur due to systematic biases, such as nonresponse error.

Explanations: Sampling error is the correct answer because it specifically refers to the discrepancy between the sample and the target population. Nonresponse error, where the respondents differ from the sample, is a type of sampling error. This error can lead to biased results if the nonrespondents have different characteristics from the respondents.

Option Analysis:

Option A: Correct. Sampling error occurs when the sample does not represent the target population, and nonresponse error is a type of sampling error.
Option B: Incorrect. Frame error occurs when the sampling frame does not accurately represent the target population, which is different from sampling error.
Option C: Incorrect. Random error refers to variability due to chance, not systematic biases like nonresponse error.
Option D: Incorrect. "Sample" is a general term and does not specifically address the error in representation.

Frequently Asked Questions

What is the difference between a population and a sample in research?

A population includes all members or elements sharing characteristics being studied, while a sample is a subset of the population used to represent the whole group.

How does random sampling help in reducing bias?

Random sampling ensures that every member of the population has an equal chance of being selected, which helps minimize selection bias and increases the likelihood of a representative sample.

What is the purpose of stratified sampling?

Stratified sampling divides the population into subgroups based on specific criteria and then samples from each subgroup to ensure representation from all segments of the population.

What is nonresponse error and how can it affect research?

Nonresponse error occurs when some individuals in the sample do not respond, leading to potential bias if the nonrespondents differ systematically from those who do respond.

How does convenience sampling differ from random sampling?

Convenience sampling selects individuals based on ease of access, while random sampling ensures each member of the population has an equal chance of being selected, making it less biased.

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