Sampling design proposal: procedures, rationale, and research objectives

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.

Random Sampling

The random sampling method of gathering data might work the very best for this study, especially if there is easy access to a number of geographically different areas in the city, state or country that the researcher is concerned with sampling. The random sampling method can be as easy as standing outside a Wi-Fi spot in any city and randomly selecting individuals to survey as they walk in or out of the facility. There are disadvantages to this methodology however, and those disadvantages include the fact that it is a very costly and time-consuming method of gathering data. Random sampling can also include a certain bias either for or against the particular study (at least in this case) due to the fact that the sample is going to target those individuals who use certain Wi-Fi hotspots, and many times if a certain hotspot is experiencing problems, all the customers of the spot will also experience problems, and vice versa of course. Such a problem is usually addressed through the controlling for random error. Controlling through random error, according to Emerson (2015) is the art of "limiting the impact that factors unrelated to the study have on what they (researchers) are seeking to measure through their research" (p. 165). Limiting the impact that the random sampling of Wi-Fi sites would have on the study would definitely be a concern for this particular study.

Convenience Sampling