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Sampling Methods

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Sampling Methods

Would you be upset if your university conducted a survey about the rising cost of student parking passes but failed to use actual students as the survey participants? Chances are, you would feel pretty underrepresented in an issue so important to your own experience. Not only is this survey important to the student community, but to the integrity of the survey itself. This hypothetical scenario sheds light on one of the most significant factors in research design; sampling methods.

After reviewing this explanation on sampling methods, you will better understand the types of sampling methods, how they are utilized in psychology, and why they are important.

  • How do researchers use sampling methods?
  • What are different types of sampling methods?
  • What are problems with sampling methods?

Sampling Methods in Research

Within all facets of applied science, especially psychological research, the selection of participants in a survey or study can be what “makes or breaks” the significance of the results. All data and observations are ultimately sourced from this representative sample of individuals. Therefore, it is crucial to ensure that those participating are a great representation of the required diversity for the population of the study at hand. The selection of these participants through sampling methods is important for both the significance of the findings, and the well-being of the target audience and consumers.

Sampling Methods in Psychology

How do researchers start identifying sampling methods for the particular study being conducted?

First, researchers must assess the content and structure of the study to select the most appropriate type of sampling method. Doing so provides criteria to follow that dictate what type of participants are needed for the research. In psychology, many studies require participants who have certain experiences, symptoms, or disorders that will ultimately pertain to the topic or phenomenon being studied.

In contrast, there is also a requirement for participant selection to be completely randomized and diverse for control groups or other means. For the study to be established as reliable and valid, the sample of participants must be representative of the target population.

Types of Sampling Methods

Now that we have discussed why sampling methods are so important to psychological research, you must be wondering what the different types of sampling methods are, and how researchers select them.

There are four main types of sampling methods used in research. Each technique is dependent on the kind of study and the population being generalized within each study. We will go over when each method is used, and the pros and cons of different sampling methods.

Stratified Random Sampling

Because populations can sometimes be disproportionate, the sample taken must also represent this in its demographics (Jackson, 2016). This means that if a population being generalized has more females than males or more seniors than youth, the sample must also simulate this to be representative. Stratified random sampling helps to ensure this by dividing a population by those subgroups, also known as strata, and then randomly selecting participants from each stratum for the most representative sample for the study.

Pros: Ensures a more exact representation of the population’s dimensions. It is more efficient in terms of size of the sample.

Cons: It can be difficult to analyze the differences between strata. It is not as simple to conduct.

Cluster Sampling

Similar to stratified sampling, cluster sampling uses a smaller group than the population to select a sample. This is mainly due to a population that is too large to select an equally representative sample from. By selecting a cluster from the population, you can get a good variety of participants to use in a sample.

A study is being conducted on California education systems. Instead of using a sample from such a large population, researchers would select a few cities in California to extract samples from, making the study more efficient and representative of the state's diverse population.

Pros: Uses fewer population sources, saves money and time, and allows for more accurate samples.

Cons: Could potentially result in biased samples. It may also leave out some underrepresented subgroups.

Convenience Sampling

As the name implies, convenience sampling is truly out of convenience to the researchers and parameters of the study. Unlike the previously mentioned sampling methods, this one is not as careful in the selection of participants, and instead uses a sample of participants from whatever source is most convenient. Imagine you are conducting a study for your research methods class. Due to your limited reach and connections, you stand outside the cafeteria and ask any of the students walking by if they would like to participate in your study. As you are only collecting participants who happen to be around at the same place and time, this would be an example of a convenient sampling method.

Pros: Cost and time-efficient, student-friendly, easy to collect participants.

Cons: High risk of underrepresentation, low accuracy and validity, inconsistent results, high risk of sampling errors.

Quota Sampling

In quota sampling, the goal is to ensure the selected sample of participants represents the population in particular qualities. However, they are also chosen through any convenient source. Just like convenience sampling, the participants are selected from wherever they can be found, but are then filtered to ensure they meet the representative criteria.

Pros: Low costs, more effort in representation, time-efficient.

Cons: High risk of selection bias in participants, not random, not generalizable to the population.

To select the one ideal for their study, researchers must assess both the pros and cons of different sampling methods to reach the most representative and valid result.

Error in Sampling Methods

What happens when sampling methods are carried out incorrectly or with unintended bias? This is known as sampling errors and can occur in any given study. These errors are common among novice researchers as well as well-established teams of professionals. However, they can be identified and avoided in future attempts.

Sampling errors may include mistakes in the selection of participants. This occurs when researchers pick out participants themselves or when participants volunteer, which can lead to the potential of biases. Later data extracted from participant results may be affected by this error, and should be avoided using a more randomized selection method.

Non-response errors can also harm the validity of the sampling methods due to the lack of participation altogether. Usually, these non-response errors are seen in sampling methods like convenience sampling because of the limited commitment from the sample.

Sample frame errors pose a threat to studies by simply selecting irrelevant samples of participants, which ultimately impacts the results and data.

Researchers must carefully analyze the features, size, and relevance of the target population they intend to sample from to avoid these common errors. In doing so, these errors are less likely to occur, and the study will result in more relative and meaningful findings.

Sampling Methods - Key takeaways

  • Sampling methods in psychology and research are the techniques used to gather a sample of participants that are representative of the target population in a study.
  • Stratified sampling is when researchers divide the population into strata and then extract a sample from each stratum (subgroup).
  • Cluster sampling is the collection of a sample through the divided clusters of equally representative participants for a sample.
  • Convenience sampling is the most flawed but also the most cost and time-efficient form of sampling.
  • Quota sampling is equivalent to convenience sampling, but uses a more representative sample of participants from a population.
  • Errors in sampling happen through participant selection, non-response, and sample frame errors.

Frequently Asked Questions about Sampling Methods

Convenience, quota, cluster, and stratified sampling.

Each technique is dependent on the kind of study being performed and must be representative of the target population.

This sampling method uses a sample of participants from whatever source is most convenient.

This sampling method works by dividing a population into subgroups, also known as strata, and then randomly selecting participants from each stratum.

In quota sampling, the goal is to ensure the selected sample of participants represents the population in particular qualities; however, they are also chosen through any convenient source.

Final Sampling Methods Quiz

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What are sampling methods used for?

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Sampling methods are techniques used to collect a specific sample of participants that are relevant to the target population of a study. 

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What are the four types of sampling methods?

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Stratified random, cluster, convenience, and quota sampling methods.

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Describe quota sampling.

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Participants are selected through convenience, but are filtered to ensure they meet the representative criteria of the population.

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Describe convenience sampling.

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Convenience sampling is the collection of a sample through any means available and without a strategy.

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Describe cluster sampling.

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Cluster sampling uses smaller groups than the population to collect a representative sample.

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Describe stratified random sampling.

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Uses subgroups/strata of the given population while accounting for the different dimensions of the population.

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A research team wants to conduct a study on income levels in the state of Texas. Which sampling method should they use?

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Cluster sampling method.

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Convenience sampling is the most valid and accurate sampling method. True or False?

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False. It is the least accurate and valid of the four.

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A class is conducting a study on personalities within their university. They have no financial resources for this study and have very little time to turn in their results. In this case what would be the appropriate sampling method?

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Convenience sampling method.

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What are some cons of stratified random sampling?

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Difficult to compute statistically, takes more time.

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What type of error occurs when the researcher selects participants, or only interested volunteers participate? 

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Selection bias/error

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What are the cons of cluster sampling?

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Potential underrepresentation, result in possible biases

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Stratified sampling method is very time-efficient and simple to analyze. True or false?

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False

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Quota sampling collects participants out of convenience but ensures the sample is representative. True or false?

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True

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What is a non-response error?

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Lack of willing participants leads to a sample that is not completely representative of the target population.

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What is random sampling?

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Random sampling is a research method that is used for picking participants for a study out of a population. 

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What is simple random sampling?

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Simple random sampling is a method where each item or person in a population has an exactly equal probability of being selected. 

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What is systematic random sampling?

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Systematic sampling is a method that uses intervals in the selection process. 

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What is stratified random sampling?

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In stratified sampling the population is split up into groups based on distinct characteristics, after which the researcher randomly selects participants in each group. 

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What is clustered sampling?

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Clustered random sampling uses clusters. It is similar to stratified random sampling; however, the population is split into many subgroups.

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Why is random sampling important?

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Among other things, it helps reduce bias. 

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Why is random sampling important? 

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Among other things, it does not require the researcher to have much technical knowledge. 

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Why is random sampling important? 

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Among other things, using random sampling ensures that the data is well-informed.

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Why is random sampling important? 

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Among other things, it allows for creating a smaller sample from a large population.

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Stratified sampling is usually ____ robust than simple.

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More

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Random sample variability is _____ when using larger sample sizes.

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Less

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Replacement refers to ____?

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Replacing the participant of the population back to the population after being selected.

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Is replacement important in large populations?

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No

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I have a population of 6000 people, and I split them up by age before picking a sample. This is an example of:

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Stratified sampling

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If i have a group of 1 million people in alphabetical order and I sample them by selecting every 100th person, this is an example of:

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Systematic sampling

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What is stratified sampling?

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When the population is divided into specific groups and then randomly sampled from those groups

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What is random sampling?

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When subjects for the research are randomly taken from the population at large

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What is the difference between random sampling and stratified sampling?

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Stratified sampling has an extra step of splitting the population into strata before the random sampling happens

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What are strata?

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The subgroups that people are divided into during stratification

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How many strata can each participant be sorted under?

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1

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What is not an advantage of stratified sampling?

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High internal validity

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What is the correct order of the first three steps of stratified sampling?

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Define population, define strata, separate population into strata

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What is the correct order of the final three steps of stratified sampling?

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List sample size, determine strata sample sizes, random sampling

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Is it necessary to follow the steps in order when using stratified sampling?

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Yes! The steps are crucial for making sure that the necessary definitions of strata and population are made before any sampling takes place. 

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How does stratified sampling reduce sampling bias?

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It makes sure that all subgroups are represented in the study's population

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True or false? Random sampling does not happen during stratified sampling. 

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True - stratified sampling happens during random sampling, but not the other way around

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When do researchers use stratified sampling?

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When they want to highlight differences in groups

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Is stratified sampling random?

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Yes - it is completely random sampling

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What is a disadvantage to stratified sampling?

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It takes more time defining and sorting the population into strata than if the researchers were not using stratified sampling

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What does it mean when something is stratified?

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It's arranged based on groups

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