Convenience sampling, also known as accidental sampling, grab sampling, or availability sampling is a common type of non-probability sampling. Non-probability sampling uses the individual judgment of the researcher and doesn’t rely on a random selection (as in probability sampling). This article covers an important type of non-probability sampling called convenience sampling. It discusses its definition, examples, advantages, disadvantages, analysis, and the reasons for using a convenience sampling technique.
Convenience Sampling Definition:
Under convenience sampling, as the name suggests, the sample is collected from that part of the population data that is readily available or which is the easiest to reach. It uses the very first primary data available to the researcher, taking participants from the most convenient part of the population.
Example of Convenience Sampling:
Contrary to popular belief there are many theoretical and practical reasons for using non-probability sampling. One of its types, convenience sampling is used for a number of reasons. For example, it can be used to gather primary data about some specific issues. For example, a company can use convenience sampling to understand what the general public thinks of its brand or what the customers think of its new packaging or design.
It can be done by stopping random people on the street or shopping malls and asking them some questions about the issue at hand. One of the latest forms of it is using social media polls, questions, and questionnaires. This way, random people can be reached in the most convenient way possible without spending any money.
Why do we use Convenience Sampling?
There are many reasons for using convenient sampling. Unavailability of time or finances is the most common of reasons. But, sometimes it is the only way out. For instance, you use it when you can’t list all the people in a population. If you are to conduct a survey about what employees of your rival company think about their employer, you can’t possibly get a list of the employees working there. So, you are will have to stand outside of that company and interview the employees coming out if its doors. These employees may not give you the most accurate picture of what you are trying to study, but it is pretty much the only way of conducting that survey.
Convenience sampling is the easiest way to know about people’s habits, points of view and, interests, likes, and dislikes.
Let’s Take an Example of Convenience Sampling:
Suppose you are trying to find out how sustainable viral marketing is going to be in the future. You can generate a list of questions, form a questionnaire of it, and send the link of that questionnaire to all your contacts via your social media or phone contacts list. The people who will be filling out that questionnaire will be the ones who were the most convenient to reach out to.
Convenience Sampling Advantages:
Convenience sampling is used in a number of places because it has several upsides. Some of them are:
- There are fewer rules to adhere to, meaning there is no specific way to collect the sample. It just needs to be from the population in question.
- It is quick and inexpensive. Unlike probability sampling, whereby you have to put in considerable time and money to get the primary data, convenience sampling is time and cost-effective.
- The participants of convenience sampling are easy to reach out to. You just have to grab participants from wherever you can (hence the name, grab sampling).
- It is easier to analyze the convenience sampling data as compared to other alternative methods. It also helps with the hypothesis generation.
Convenience Sampling Disadvantages:
Convenience sampling may not give you the most accurate results. It has numerous other drawbacks as well. These are:
- Convenience sampling sometimes gives biased results. In the employee satisfaction example, you may end up having over or under-represented results. The employees volunteering to answer may be the ones who hold some grudge against the company and they may not represent the true picture of what employees of that company actually think about it.
- The sample itself or the results of the survey cannot be applied to the whole population. In other words, convenience sampling leaves researchers unable to generalize the results. This is the reason why it is sometimes prohibited to use convenience sampling in dissertations.
- The sampling errors are too many. The participants can be biased or they may belong to only a particular part of the whole population etc. All of this puts the results of the research in serious jeopardy.
How to analyze it efficiently?
There are several ways to analyze convenience sampling data. You can use any method of your choice. But, the results cannot always be replicated or applied to a whole population.
In order to get somewhat accurate results, you should take more and more samples. If possible, repeat the survey. Be sure to cross-validate at least half of the data whenever you are using big samples. If possible, use probability sampling along with convenience sampling.
It is best to use probability sampling as it is more accurate but when the only resort you have is to use convenience sampling, use the hacks mentioned above to reduce the biases to some degree.