Random selection refers to a process that researchers use to pick participants for a study. When using this method, every single member of a population has an equal chance of being chosen as a subject.
This process is an important research tool used in psychology research, allowing scientists to create representative samples from which conclusions can be drawn and applied to the larger population.
Examples of Random Selection
Random selection is a crucial technique in psychology research to ensure that samples are representative of the population, thus enhancing the generalizability of the findings. Here are a few brief examples of how random selection can be used in different areas of psychology research:
Survey Research on Mental Health
A researcher wants to study the prevalence of anxiety disorders among adults in a city. They use random selection to choose a sample of adults from the city’s population registry. This ensures that every adult in the city has an equal chance of being selected, making the sample representative of the entire adult population.
Experimental Research on Cognitive Processes:
To investigate the effects of sleep deprivation on memory, a researcher randomly selects participants from a university’s student population. By randomly assigning these students to either a sleep-deprived group or a control group, the researcher ensures that any differences in memory performance are likely due to the manipulation of sleep rather than pre-existing differences between groups.
Developmental Psychology Studies
A study aims to understand the development of language skills in toddlers. The researcher randomly selects toddlers from several daycare centers in a region. This random selection helps ensure that the sample includes children from diverse backgrounds, leading to more generalizable findings about language development.
Clinical Trials for Psychological Interventions
In testing a new therapeutic intervention for depression, a researcher randomly selects participants from a pool of individuals diagnosed with depression. Participants are then randomly assigned to either the intervention group or a control group (e.g., receiving standard care). This random selection and assignment help control for potential confounding variables and biases.
Social Psychology Research
To study the impact of group dynamics on decision-making, a researcher randomly selects employees from different departments of a large corporation. By using random selection, the researcher can ensure that the sample is not biased towards any particular department, making the findings more applicable across the entire corporation.
These examples illustrate how random selection helps create representative samples and enhances the internal and external validity of psychological research.
Random Selection vs. Random Assignment
It is important to note that random selection is not the same as random assignment. While random selection involves how participants are chosen for a study, random assignment involves how those chosen are then assigned to different groups in the experiment.
Many studies and experiments actually use both random selection and random assignment.
For example, random selection might be used to draw 100 students to participate in a study. Each of these 100 participants would then be randomly assigned to either the control group or the experimental group.
Reasons to Use Random Selection
What is the reason that researchers choose to use random selection when conducting research?
Some key reasons include:
Increased Generalizability
Random selection is one way to help improve the generalizability of the results. A sample is drawn from a larger population. Researchers want to be sure that the sample they use in their study accurately reflects the characteristics of the larger group.
The more representative the sample is, the better able the researchers can generalize the results of their experiment to a larger population.
By randomly selecting participants for a study, researchers can also help minimize the possibility of bias influencing the results.
Reduced Outlier Effects
Random selection helps ensure that anomalies will not skew results. By randomly selecting participants for a study, researchers are less likely to draw on subjects that may share unusual characteristics in common.
For example, suppose researchers were interested in learning how many people in the general population are left-handed. In that case, the results might be skewed if subjects were inadvertently drawn from a group that included an unusually high number of left-handed individuals.
Random selection ensures that the group better represents what exists in the real world.
Sources:
Hilbert, S. (2017). Random selection. In: Zeigler-Hill, V., Shackelford, T. (eds) Encyclopedia of Personality and Individual Differences. Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8_1344-1
Martínez-Mesa, J., González-Chica, D. A., Duquia, R. P., Bonamigo, R. R., & Bastos, J. L. (2016). Sampling: how to select participants in my research study? Anais brasileiros de dermatologia, 91(3), 326–330. https://doi.org/10.1590/abd1806-4841.20165254