Use of proper sampling techniques to research studies

Abstract

This article extensively examines several sampling strategies, emphasising probability and non-probability sampling approaches. Sampling is essential in research as it influences the degree to which research findings accurately represent and can be applied to a larger population. This article provides a definition of probability sampling and explores its different approaches. The text highlights the benefits of probability sampling, such as its capacity to guarantee impartial selection and facilitate statistical inference. Furthermore, this article delves into the constraints and factors to be taken into account regarding probability sampling, including the need for resources and the possibility of mistakes in sample frames. Subsequently, this paper examined non-probability sampling strategies and investigated methodologies such as convenience sampling, purposive sampling, and quota sampling. This article examines the fundamental concepts of non-probability sampling and highlights its specific applicability in investigating groups that are rare or challenging to access. A comprehensive examination was undertaken to assess the benefits and drawbacks of non probability sampling, with a particular focus on problems such as researcher bias and the absence of statistical generalizability. This article offers a thorough examination of probability and non-probability sampling approaches, allowing scholars to acquire a more profound comprehension of the benefits, constraints, and suitable uses of each approach. It acknowledges the significance of choosing the most suitable sampling method according to research goals, available resources, and the attributes of the target population. In conclusion, this work offers significant resources for researchers who wish to make well-informed choices on sampling procedures in their research.