Sampling and Probability in Research Quiz

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Questions and Answers

What is the term used for persons, objects, or events, on whose properties or characteristics our research will focus?

Participants

Variables

Elements

Units of analysis (correct)

In qualitative research, what is the primary focus when selecting people to study?

Diversity of the sample

Statistical representativeness of the sample

Random selection of participants

Participant observation (correct)

What is the term for a population consisting of a specifiable number of elements?

Finite population (correct)

Random population

Infinite population

Representative population

What is the purpose of probability sampling?

To specify the probability of each element being included in the sample, allowing reliable conclusions about the population Signup and view all the answers

What is the role of a sampling frame in research?

It is a list of elements in a population from which a sample is drawn Signup and view all the answers

What is the limitation of nonprobability sampling?

It does not allow the determination of the likelihood of an element being selected, posing limitations for drawing reliable conclusions about a population Signup and view all the answers

What is the formula for determining the number of possible combinations of elements drawn at a time from a population of size $n$?

$C(n, r) = \frac{n!}{r!(n-r)!}$ Signup and view all the answers

Which sampling method gives each individual in the population an equal chance of being selected?

Simple random sample Signup and view all the answers

What impact does the sample size have on the risk of generalizing from a sample to the population?

The risk decreases as the sample size increases Signup and view all the answers

What is a simple random sample?

A sample in which each element in the population has an equal chance of being selected Signup and view all the answers

When is a stratified random sample most useful?

When we want to ensure that our sample is representative of our population in certain specifiable ways Signup and view all the answers

What is disproportionate sampling?

A sampling strategy in which all elements have known, but different, probabilities of being included in the sample Signup and view all the answers

When is proportionate sampling used?

When the sample drawn from each stratum is adjusted so that the proportion of elements in the sample is equal to the proportion of the whole population contained in that stratum Signup and view all the answers

What is the key feature of any probability sample?

Being able to specify the probability that any given element will be included Signup and view all the answers

What is the crucial feature of disproportionate sampling?

All elements have known, but different, probabilities of being included in the sample Signup and view all the answers

In disproportionate sampling, what is the crucial feature of any probability sample?

The ability to specify the probability that any given element will be included Signup and view all the answers

When using disproportionate sampling to focus on a specific ethnic group, what is a potential consequence for the overall sample?

The sample may no longer be representative of the ethnic distribution within the population Signup and view all the answers

In a population with a small percentage of a minority group, how can disproportionate sampling be used to ensure a relatively large number of that minority group in the sample?

Assign a higher probability of selection to the minority group and a lower probability to other groups Signup and view all the answers

Which sampling method involves dividing the population into clusters and selecting a random sample of clusters?

Cluster sampling Signup and view all the answers

What is a potential drawback of systematic sampling?

It may lead to biased results if the list is ordered in some way Signup and view all the answers

What distinguishes cluster sampling from stratified sampling?

Clusters contain approximately equal numbers of individual elements, unlike strata in stratified sampling Signup and view all the answers

What is the primary assumption underlying a quota sample?

The researcher ensures that various elements of the population are included in the sample by establishing quotas for each subgroup. Signup and view all the answers

What is the key feature of purposive sampling?

The assumption that the researcher has enough skill to select subjects who ought to be included in the sample. Signup and view all the answers

What distinguishes snowball sampling from other sampling methods?

Subjects recommend others like themselves for inclusion in the study. Signup and view all the answers

In what scenario is snowball sampling most often used?

Qualitative research involving illegal or illicit activities. Signup and view all the answers

What is the main purpose of purposive sampling?

To select subjects who are 'typical' of the population in question based on the researcher's judgment. Signup and view all the answers

What distinguishes snowball sampling from random sampling?

It is not concerned with statistical representativeness. Signup and view all the answers

Which sampling method is commonly used to study public opinion or voter preference in large, geographically dispersed populations?

Cluster sampling Signup and view all the answers

What type of sampling involves individuals who accidentally come into contact with the researcher?

Accidental sampling Signup and view all the answers

What is a potential risk associated with cluster sampling?

Increased risk of errors when generalizing from the sample to the population Signup and view all the answers

What distinguishes qualitative sampling procedures from quantitative sampling procedures?

Qualitative sampling procedures are always nonrandom and use only nonprobability sampling methods. Signup and view all the answers

What is the primary focus of qualitative researchers when selecting people to study?

Finding meaning in human experiences Signup and view all the answers

Which sampling method involves individuals offering to take part in the research?

Volunteer sampling Signup and view all the answers

What is a common practice in qualitative research but not in quantitative research?

Using more than one sampling approach in a research project Signup and view all the answers

What type of knowledge do people who participate in qualitative studies usually have of the phenomenon being studied?

Direct and personal knowledge Signup and view all the answers

What is the key consideration for a researcher when selecting a population for sampling?

The representation of the population in the sample Signup and view all the answers

When investigating citizen attitudes toward the police for the purpose of supporting a bond issue, which population might be most appropriate to sample?

The list of registered voters Signup and view all the answers

What is the risk of overgeneralizing sample data according to the text?

Giving the impression that results apply to a larger population Signup and view all the answers

In what scenario can generalizations be made beyond the sampled population?

When the sample is randomly selected Signup and view all the answers

What is the consequence of sampling Chicago police officers and then applying the findings to police officers in other cities?

The findings are only applicable to Chicago police officers Signup and view all the answers

In qualitative research, what does data saturation indicate?

The point at which the researcher should stop collecting data Signup and view all the answers

What is the primary focus of theoretical sampling in grounded theory?

Generating a theory Signup and view all the answers

What is the main objective of probability sampling?

Allowing determination of the sample size required to meet specified limits of sampling error Signup and view all the answers

For quantitative research, what is the recommended minimum sample size?

30 Signup and view all the answers

What is the purpose of snowball sampling in research?

Participants recommending others to the researcher Signup and view all the answers

Study Notes

Sampling and Probability in Research

Drawing small samples from large populations with sampling without replacement is common due to minimal changes in probability.
Probability of drawing any two particular names from a population of five names can be determined by listing all potential combinations of two names.
A formula has been developed for determining the number of possible combinations of elements drawn at a time from a population of size n.
The risk of generalizing from a sample to the population decreases as the sample size increases.
Probability sampling provides more assurance that the sample is representative of the population as the number of elements sampled increases.
A simple random sample gives each individual in the population an equal chance of being selected, making all combinations equally probable.
Creating a sampling frame for a simple random sample can present challenges, especially in maintaining an accurate and complete list of population elements.
Lists identifying a population may be biased, inaccurate, or non-existent, requiring careful construction and evaluation for accuracy.
Various techniques, such as using random numbers tables or computer programs, can be employed to select a sample of the desired size from a population.
Technology, such as the Research Randomizer and HotBits, offers alternatives for generating random samples, impacting research designs and sampling methods.
The Research Randomizer provides pseudorandom numbers suitable for most research projects, while HotBits generates genuine random numbers from quantum mechanical processes.
The impact of technology on research designs, sampling methods, and data collection is discussed in more detail in Chapter 12.

Sampling Techniques in Research

Cluster sampling divides a population into subgroups of equal size, with each element having an equal chance of being selected as part of a cluster.
In stratified sampling, strata are defined, and individual elements are sampled within each stratum.
Cluster sampling is commonly used to study public opinion or voter preference in large, geographically dispersed populations.
It may involve defining the population as a collection of city blocks or congressional districts, with each block or district serving as a cluster of citizens.
Multistage sampling involves applying cluster sampling in successive stages or combining it with random sampling techniques.
Multistage sampling can generate a sample of respondents located in specific districts, making it cost-effective and less labor-intensive.
However, cluster sampling increases the risk of errors when generalizing from the sample to the population, as some clusters and elements may have no chance of being included in the final sample.
Nonprobability sampling offers economy and convenience but lacks the ability to accurately estimate sampling error and evaluate biases.
Accidental sampling, a type of nonprobability sample, involves individuals who accidentally come into contact with the researcher.
Person-in-the-street interviews are typical of accidental samples but are influenced by biasing factors such as time and place.
Nonprobability sampling includes accidental, quota, purposive, and snowball sampling, each with its own limitations and risks.
Making statements about a population based on nonprobability sampling data is risky due to the inability to determine the probability of inclusion and the lack of inferential statistics.

Sampling Methods and Sample Size in Research

Volunteer or convenience sampling is a nonprobability sampling method where participants contact the researcher to participate, with the researcher having no control over who participates.
Snowball and purposive sampling methods work the same as in nonprobability quantitative research, with participants recommending others or the researcher intentionally choosing individuals with direct knowledge of the phenomenon.
Theoretical sampling is used to generate a theory, commonly in grounded theory, by choosing individuals who best represent the constructs in the study.
Theoretical sampling is complex and resource-intensive, often leading to researchers struggling to understand how to carry it out properly.
The sample size in research should be large enough to permit data analysis within the researcher's time and budgetary limits.
For quantitative research, the sample size should not be less than 30, with most researchers preferring a sample size closer to 100, and for extremely large populations, a sample size of up to 1,500 may be desirable.
Probability sampling allows for determination of the sample size required to meet specified limits of sampling error.
In qualitative research, the sample size may change as the research progresses; researchers must sample long enough to gather rich, detailed data.
Data saturation in qualitative research occurs when no new information is obtained from interviews or observations, and it indicates the point at which the researcher should stop collecting data.
Qualitative researchers often rely on judgment and experience to determine the point of saturation, and few share how they determined it, but they must convince the reader that the sample was appropriate and sufficient to justify the findings.
The selection of the actual population to be sampled in research depends largely on the objectives of the researcher, and many research questions can be answered by selecting samples from different populations.
The objective of any sampling plan, whether quantitative, qualitative, or mixed methods research, is to obtain a sample of the relevant population that is large enough to permit data analysis and can be studied within the researcher’s time and budgetary limits.

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Description

Test your knowledge of sampling and probability in research with this quiz. Explore concepts such as simple random sampling, probability calculations, sampling frames, and the impact of technology on research designs and sampling methods.