Quota and random sampling methods for data collection

Sampling Design

There are a number of methods that can be effectively used to gather data in order to ascertain thesis or answer research questions. Determining which methodology to use is at the behest of the researcher and should be determined as part of the overall design of the study. In order to gather valid and reliable data, sampling methods such as cluster, quota, simple random, systematic, stratified, non-probability and probability, and diversity sampling have all been created, and effectively used, to assist the researcher in his/her endeavors. Dos Santos and Beck (2015) found that regarding sampling methods "comparing the performance of several techniques over several problems are rarely found" (p. 624). Since a performance comparison would take a lot of time and effort to complete this study will discuss a few of the methods that are being considered for this study only. The discussion will describe the technique being considered as well as the advantages and disadvantages of the specific sampling method.

Quota Sampling

There are a number of quota methods that can be used to supply valid results (or results that measure what they are supposed to measure) including proportionate quota sampling and non-proportionate sampling. The proportionate sampling method is used when the population distribution is known but minority groups in the sample may not be measured enough. The non-proportionate sampling method is used when the sample or variable characteristic within the minority group is widely varied. For this study, the regular quota sampling methodology might be the best of the three quota sampling methods to use. The regular quota sampling method allows access to a wide population, including the minority groups within the sample.

Convenience Sampling

Convenience sampling usually takes place when the researcher does not have the time or money to fund extensive research methods (hence the word "convenience"). Convenience sampling methods usually comes in three flavors; snowball, expert, and convenience. Snowball methods are used when a participant in the study is asked to recommend a friend or acquaintance who (in this case) also uses Wi-Fi hotspots in a regular manner, and then interviewing that friend or acquaintance as another participant in the study. The expert methodology would be if the researcher was considered and expert on the area of interest and the expert provided all of his or her own data. Expert methodology is also referred to as judgement sampling. Finally, convenience sampling can be used when participants cannot be actively engaged, which might work well for this particular study. A good example of why convenience sampling may work for this study is the Kwok et al. (2015) study that used a cross-sectional survey mailed out to mothers of children aged two to six that demonstrated a return rate of 82%. If this study could mail out surveys to only regular users of Wi-Fi and get an 82% return rate, that would be very productive. However, the immediate thought that comes to mind is that there is usually a price to be paid for convenience, and in this case the price to be paid would be that the validity of the study might well be harmed by the use of convenience sampling.

Summary

Two other sampling methods are also being considered; selective sampling and theoretical sampling. The selective sampling method focuses on particular groups or subjects, and the theoretical method focuses on theories that are emerging. Both of these can be used in conjunction with other considered methodologies, although it is likely that the researcher will likely stick with the convenience methodology that allows for the mailing out of surveys to Wi-Fi users. It seems as if the convenience sampling method would work the very best at this point for this specific study.