Why Aren’t Convenience Samples Usually Representative of the Population
Convenience Sampling: Definition, Method and Examples
By Julia Simkus, published Jan 30, 2022
Convenience sampling (also chosen adventitious sampling or grab sampling) is a method of non-probability sampling where researchers will choose their sample based solely on the convenience.
Non-probability sampling means that researchers choose the sample equally opposed to randomly selecting information technology, so not all members of the population have an equal gamble of participating in the study.
is the participants you select from a target population (the group you are interested in) to brand generalizations about. Equally an entire population tends to be too large to work with, a smaller grouping of participants must act as a representative sample.
means the extent to which a sample mirrors a researcher’southward target population and reflects its characteristics (e.thousand. gender, ethnicity, socioeconomic level). In an effort to select a representative sample and avoid sampling bias (the over-representation of 1 category of participant in the sample), psychologists utilize a variety of sampling methods.
ways the extent to which their findings tin be applied to the larger population of which their sample was a part.
At that place is little judgment or speculation when choosing the representative sample in convenience sampling; the sole choice criteria is ease of obtaining a participant.
This can be dependent on costs, geographic distributions, or facility of obtaining data. Some examples of convenience sampling could include recruiting friends to participate in your study, collecting data from locations that are nearby, sending a survey in the mail, or sharing a link on social media.
For example, if high schoolhouse students are conducting a report on the average consumption of pizza in the cafeteria each week, they could telephone call their classmates and inquire how many slices they consume during the week.
Applications: When is it used
- When researchers are more than concerned with the number of responses, and not the actual representativeness of the sample.
- When budgeting is tight and researchers want a low-cost method to collect data.
- When pilot testing.
- When observing habits, opinions, and viewpoints of a target audience.
- When collecting feedback on diverse brands or organizations.
- When researchers don’t have access to the full target population for a representative sample.
How to Finer Convenience Sample?
- Understand who is the target population that will help your inquiry and plan out where you could go to speak to these people.
- Take multiple samples as a larger sample size volition reduce the chance of sampling mistake.
- Include both qualitative and quantitative questions in your survey or questionnaire.
- Repeat the survey to ensure the accuracy of your results.
- Utilise convenience sampling along with probability sampling to supplement your research.
Quick, elementary method of data drove
Convenience sampling is benign when fourth dimension is a constraint as it is a uncomplicated method and takes minimal endeavor.
Many researchers prefer convenience sampling as there are few rules to follow, and information technology allows researchers to generate large samples in brusque periods of fourth dimension.
Convenience sampling has petty cost involved equally no travel or extensive planning is necessary. This method is particularly useful for students who are on a upkeep equally information technology requires minimal toll and feel.
Readily available sample
Convenience sampling tends to exist collected with populations that are easily attainable.
As the data is readily available, researchers tin can utilise convenience sampling to acquit pilot data or explore a hypothesis that might be tested in time to come inquiry.
And, if more participants need to be added at a later date, researchers can effortlessly create more than samples.
Bias is the primary disadvantage of convenience sampling, and in some cases, this sole limitation can outweigh the advantages. Collected samples may not be representative of the population of interest and thus, the results cannot exist generalized to a greater population.
Some examples of the types of bias that could result from convenience sampling include sampling bias, selection bias, and positivity bias.
Low external validity
Due to the loftier probability of bias in convenience sampling, your enquiry findings volition likely take trivial credibility in the greater research manufacture.
- Collect symptom profiles of patients with COVID-19 (Shush et al., 2020).
- Estimate immunity to vaccine preventable diseases in children in Victoria, Commonwealth of australia (Kelly et al., 2002).
- Examine the physical, mental, and cognitive function of centenarians (Richmond et al., 2011).
- Written report eating disorder symptoms and weight and shape concerns of women ages fifty and above (Gagne et al., 2012).
- Examine JUUL use patterns, other tobacco product utilise, and reasons for use amid users (Leavens et al., 2019).
- Characterize patterns of caffeine consumption among U.S. college students (Norton, Lazev, & Sullivan, 2011).
- Evaluate at-hazard and problem gambling amid adolescents (Castren et al., 2015).
Ofttimes asked questions about convenience sampling
1. What is a convenience sample in qualitative research?
Convenience sampling is often used for qualitative inquiry. Researchers utilise this sampling technique to recruit participants who are convenient and easily attainable.
For case, if a company wants to get together feedback on their new production, they could become to the local mall and approach individuals to ask for their opinion on the production.
They could take people participate in a short survey and enquire questions such as ‘take you heard of 10 brand?’ or ‘what do you call up of x production?
ii. Why is convenience sampling biased?
Because researchers are usually unable to generalize the results of the survey to the population as a whole, the estimates derived from convenience samples are oft biased.
At that place is the possibility of over or under representation as the sample poorly represents the target population. Since subjects are selected because they are easily accessible, researchers tend to not gain a range of participants each time they collect information, and they also may exclude relevant demographic subsets from the results.
three. How to reduce bias in convenience sampling?
There are many strategies that researchers can employ to reduce bias when convenience sampling. Ane of the most successful ways to reduce bias is to employ convenience sampling along with probability sampling.
Probability sampling uses a random selection process so anybody in your population has an equal chance of being chosen. Using both convenience sampling and probability sampling together will enable researchers to describe accurate conclusions by reducing, or fifty-fifty eliminating, bias.
Other techniques to effectively convenience sample include:
- taking multiple samples as a larger sample size will reduce the chance of sampling error;
- repeating the survey to ensure the accuracy of your results;
- including both qualitative and quantitative questions in your survey or questionnaire;
- and taking multiple samples as a larger sample size will reduce the hazard of sampling mistake.
4. What is the deviation between convenience and purposive sampling?
Purposive sampling and convenience sampling are often used interchangeably, simply they are ii different methods. Researchers in convenience sampling will recruit participants based solely on convenience and accessibility.
They volition leverage individuals that can be accessed with minimal try. On the other hand, researchers in purposive sampling will use judgment and planning to select a sample of individuals that will benefit their study.
Researchers must take prior knowledge about the purpose of the study and then they can cull participants that will fit certain characteristics and represent the greater population of interest.
About the Author
Julia Simkus is an undergraduate student at Princeton University, majoring in Psychology. She plans to pursue a PhD in Clinical Psychology upon graduation from Princeton in 2023. Julia has co-authored two journal manufactures, i titled “Substance Employ Disorders and Behavioral Addictions During the COVID-19 Pandemic and COVID-nineteen-Related Restrictions,” which was published in Frontiers in Psychiatry in April 2021 and the other titled “Food Addiction: Latest Insights on the Clinical Implications,” to be published in Handbook of Substance Misuse and Addictions: From Biology to Public Health in early 2022.
How to reference this article:
How to reference this article:
Simkus, J. (2022, Jan 30).
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Why Aren’t Convenience Samples Usually Representative of the Population