While there are many advantageous to convenience sampling, there are still some obvious drawbacks to this method. This form of sampling allows researchers to formulate theories quickly. However, they risk getting biased results as researchers have a tendency to treat the data as accurate depiction of the general public, though typically the data is not representative of the entire population.
Quick Formulation of Theories
Because convenience sampling is fast and easy, researchers can swiftly gather their data and begin to extrapolate theories from the data. This form of sampling allows for a faster analysis, permitting researchers to focus on the more important aspects of their experiment instead of calculating the best way to obtain a population sample. Because this type of data collection is literally done at the convenience of the researcher, it is perfect for quick studies, and is often used in preliminary surveys to demonstrate a need for a better understanding of the research material. The difference in cost is another pro of this method; often times studies are not granted a large budget and researchers are forced to survey the population at hand.
One of the major drawbacks to this form of sampling is the opportunity for bias to cloud the results of the survey. For example, a researcher looking to predict who will win the next election may only survey an area close to them, and ignore the fact that the region is located in the southern United States and therefore will likely have a more conservative slant. Personal prejudices may also creep into the data, as a surveyor may not distribute questionnaires to certain ethnic groups. These factors often lead to skewed data collection, rendering the data useless for tracing trends throughout the entire population.
Misrepresentation of Data
Occasionally researchers will ignore the fact that they did not complete a random survey, and will use the information to prove facts that are not necessarily true. One example of this misrepresentation is if certain magazine subscribers are polled on political opinion, when the magazine appeals to a more liberal sect of the populous. Because a national magazine subscription will have a large pool of subscribers and the people surveyed could be selected at random, researchers might be tempted to use the results of this poll as a representation of the entire populationís view. Nevertheless, because the magazine appeals to only a select group of people, it is still considered a convenience sampling and will have a liberal slant.
Because of the flaws found in this form of sampling, scientists cannot draw concrete conclusions from their data. In order to be a truly accurate study, any statistical data must include all facets of the population. By missing portions of the general populous, researchers are only able to form incomplete conclusions. One example would be polling only knitting clubs, which is typically frequented by women. Researchers would not be able to draw conclusions on what most men thought, as they would be underrepresented in this arena, and any data collected would not allow them to reach accurate conclusions.
While there are some pros to implementing this type of sampling in research, there are several cons. Overall, it depends on whether the researcher needs to gather data quickly and cheaply, or wants a more thorough understanding of what the general populace would think on whether or not they use this sampling or another type.