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Critically Discuss Sampling Strategies in Qualitative, Quantitative and Mixed Methods Research

Autor:   •  June 15, 2017  •  Research Paper  •  1,702 Words (7 Pages)  •  504 Views

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Introduction

Sampling is an important element in all academic researches because it influences the reliability and validity of the researches (Camic, Rhodes, & Yardley, 2003). Sampling generally means the selection of participants, units or settings to be investigated. There are basically three types of research methods, namely qualitative, quantitative and mixed methods research. While conducting different kinds of studies, researchers tend to adopt different sampling strategies because of the different goals of different research approaches. This essay intends to discuss the sampling strategy in qualitative, quantitative and mixed methods research. By analyzing the various purposes of quantitative and qualitative researchers, the sampling strategies used in qualitative and quantitative researchers, as well as their strengths and weaknesses are discussed. Besides, the mixed methods research which combines both probability and non-probability sampling strategy is also discussed.

Quantitative research and sampling strategy

Before discussing the sampling strategies of researches, it is necessary to understand the objective of the researches. Although selecting a study sample to ensure the effectiveness and ethics is important for all academic researches, the goal for quantitative researches is to draw a representative sample from the population (Teddlie and Yu, 2007). To ensure that the research findings can be generalized back to the population, quantitative researches therefore strive for random sampling selection method (Delice, 2010). Therefore, researches need to include different types of people in their quantitative studies to achieve the goal of inferring from one sample to a population. In quantitative researches, the researchers need to create paradigms which are closely associated with the selection of research techniques. To put it more explicitly, paradigms place lots of emphasis on the generalizability and reliability of the research findings. In order to achieve data reliability and generalizability, it is essential for quantitative researchers to pay special attention to the selection of sample representatives (Henn, Weinstein and Foard, 2006).

The basic sampling strategies are probability and non-probability approaches. Non-probability sampling approach means that the population is not selected in a mathematically random way (Henn, Weinstein and Foard, 2006). Different types of non-probability approaches include accidental sampling, quota sampling, judgmental sampling and snowball sampling. Non-probability sampling is criticized for its limited ability to generalize data because nonrandom samples are selected (McNeil & Chapman, 2005). Probability sampling, on the other hand, can generalize representative sample because there is a specifiable chance for the populations in each unit to be selected. Compared with non-probability sampling, probability sampling can enable the researchers to make the accurate generalization to the population under study. Therefore, probability sampling is suitable for quantitative researches.

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