Walking through the mall, a person with a clipboard asks you to answer some questions. You respond with your opinions, and the questioner records them. You have now just become part of a population sample in psychology. But what does that mean?
- First, we will define what a sample in psychological research means.
- Next, we will focus on stratified sampling in populations used in research.
- After, we will identify the other methods of sampling in psychology.
- Lastly, we will define and understand what bias and generalisations can occur in sampling.
Sample in Psychology Definition
Some studies target the entire human population, while others are interested only in a smaller group, for example, people from specific age groups or certain professions, and so on.
In psychology, the population is also called the target population. The population is the group of people in which a researcher is interested.
Usually, researchers can't recruit the entire population to participate in their studies. Therefore, researchers instead select a small group within the population called the sample. This method in psychology is called sampling.
The sample drawn should represent the population in which the researchers are interested in making generalisations about the population. Ideally, researchers would like to select a sample with the greatest representativeness and minimal bias. Researchers can then generalise the results to the target population with greater confidence.
But what's the difference between a population and a sample? Aren't they the same thing? No, they are different! Remember, a population is an entire group that researchers are concluding. Differently, a sample is a specific group that the data is being collected.
Types of Sampling in Psychology
Two different types of sampling can be done within psychological research -- probability and non-probability.
Probability sampling means that every member of the population has a chance of being selected and is mainly used in quantitative research. What if you wanted to have results that represented the whole population? These desired results can be attained when using probability sampling. Probability allows researchers to make a strong inference about the whole group of interest.
In probability sampling, if you had a population of 100 people, each person would have odds of 1 out of 100 of being chosen!
In non-probability sampling, individuals are selected based on non-random criteria. Using non-probability sampling means that not all individuals have an equal chance of being included. Non-probability sampling is considered to be a cheaper option and much easier. While cheap and easy sounds great for researchers, there is a high sampling risk (meaning that inferences made about the population are weak from the samples taken, and conclusions will be ruled as limited).
Exploratory and qualitative research use non-probability sampling, where the aim is not to test a hypothesis about a broad population but instead to create an initial understanding of an under-researched population (usually also small).
Sampling friends, co-workers, or shoppers at a store, are all examples of non-probability sampling.
Stratified Sampling in Psychology
A stratified sample is one in which researchers select participants according to their frequency in the target population. The researcher identifies the different groups that make up the target population and calculates the proportions needed to make the sample representative.
The identified groups are called strata (or subgroups), such as gender or age. Participants are randomly selected from each stratum in proportion to their occurrence in the population. Therefore, the sample should reflect the relative percentages of subgroups in the population.
- Unlike opportunity sampling, this method is more likely to represent the underlying population, but it is constrained by our understanding of which subgroups are essential.
- However, complete representation is impossible because stratification is not perfect. Researchers may not have perfect information about the composition of their target population.
- Stratified sampling is time-consuming. As a result, we rarely see a stratified sampling in psychological research.
Sampling Methods in Psychology
While stratified seems to be the go-to of sampling techniques, there are several different types depending on the research being conducted: opportunity, voluntary, random, and systematic.
Sampling Techniques Psychology: Opportunity Sampling
An opportunity sample is a sample that is recruited based on whoever is available.
We can obtain an opportunity sample by asking members of the population if they are interested and willing to participate in the study.
- Evaluation is the quickest and most convenient way to obtain a sample because participants are recruited based on availability.
- However, there may be unavoidable bias since the sample is essentially self-selected.
- Opportunity sampling has been criticised for its lack of representativeness and poor generalisability to the target population.
You are taking a sample of fellow students coming from the library. You are taking the opportunity of the students coming from the library as your sampling group.
Sampling Techniques Psychology: Voluntary Sampling
A voluntary sample is a sample recruited by self-selection. In other words, participants self-select and contact the researcher. We obtain voluntary samples through word of mouth or advertising.
- Volunteer sampling is a quick and inexpensive way to obtain many potential participants.
- However, volunteer sampling also runs the risk of bias, similar to opportunity sampling, because the sample is essentially self-selected.
Have you watched those talent shows on television, such as singing competitions? When the host asks the audience at home, you, to send a text message of your favourite singer, this is an example of voluntary sampling.
The drawback here is that only the viewers who have strong opinions on who should be the winner will send their votes in.
Voluntary sampling is when researchers seek volunteers to participate in studies. Volunteers can be engaged in person, on the internet, or through public postings. Researchers using voluntary sampling typically make little effort to control sample composition.
Fig. 1 Texting in your vote for the next big singing sensation is voluntary sampling.
Sampling Techniques Psychology: Random Sampling
A random sample is one in which everyone in the target population has an equal chance of being selected.
One possible method for selecting a random sample is the lottery method. Researchers assign a number to each potential participant and then create a list of random numbers to select participants for the random sample.
- Random sampling is arguably the best sampling method because it will likely provide the most representative sample and generalisable results.
- In addition, random samples are free from bias on the researcher's part, as the researcher does not influence the selection of participants.
- Nevertheless, even a random sample is biased if selected individuals refuse to participate.
- Moreover, a random sample is difficult to achieve because the recruitment process takes time and resources.
Sampling Techniques Psychology: Systematic Sampling
A systematic sample is selecting participants according to a set of patterns.
To draw a systematic sample, it is possible to list all the population members and then determine the desired sample size. If you divide the number of people in the target population by the desired sample size, you will get a number we call n. If you select every nth name, you will get a systematic sample of the size you want. For example, if you're going to draw a sample of 100 students from a university with 1,000 students, n = 1000/100 = 10, you can take every tenth name.
- Systematic sampling is an objective method that can greatly reduce researcher bias.
- However, as with random sampling, systematic sampling runs the risk of bias if selected individuals refuse to participate.
- In addition, systematic sampling requires a complete list of the population, which is difficult to obtain and time-consuming.
Sampling Techniques Psychology: Volunteer Sampling
Voluntary sampling is when researchers seek volunteers to participate in studies. Volunteers can be engaged in person, on the internet, or through public postings. Researchers using voluntary sampling typically make little effort to control sample composition.
Have you ever been walking a busy street when someone calls out to you to please take their survey on some particular issues such as local government or community changes? The person who is taking the survey from volunteers is using volunteer sampling.
Biased Sample in Psychology: Definition
Sampling bias happens when some members of a sample population are more likely to be selected in a sample than others. Sampling bias limits the generalisability of sample findings because it is a threat to external validity (specifically population validity).
Fig. 2 Asking just these students' survey questions would be a biased sample if the hypothesis required asking the whole school.
A survey of high school students being given out to measure teenage use of illegal drugs will be a biased sample. But why is that so? This surveying does not include other populations, such as home-schooled students or dropouts. A sample is also biased if certain members are underrepresented or overrepresented relative to others in the population, and in this case, those are the students who are schooled in their homes or those who never graduated.
Generalisation occurs when applying the results from a study to the broader target population. It is based on the assumption that the findings from the original sample will be the same for everyone else in the target population. This can be seen in the home-schooled students in the prior example.
Sampling Psychology - Key takeaways
- In psychology, the population is also called the target population. The population is the group of people in which a researcher is interested.
- Two different types of sampling can be done within psychological research -- probability and non-probability.
- A stratified sample is one in which researchers select participants according to their frequency in the target population.
- While stratified seems to be the go-to of sampling techniques, there are several different types depending on the research being conducted: opportunity, voluntary, random, and systematic.
- Sampling bias happens when some members of a sample population are more likely to be selected in a sample than others.
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