Description: Probabilistic sampling is a sampling technique in which each member of the population has a known probability of being selected. This methodology is based on statistical principles that ensure the sample is representative of the total population, allowing valid inferences to be made about it. There are different types of probabilistic sampling, such as simple random sampling, systematic sampling, stratified sampling, and cluster sampling. Each of these methods has its own characteristics and is chosen based on the study’s needs and the nature of the population. The main advantage of probabilistic sampling is that it minimizes bias in sample selection, which increases the validity and generalizability of the results obtained. Additionally, it allows for the calculation of sampling error and the establishment of confidence intervals, which are fundamental in quantitative research. In summary, probabilistic sampling is an essential tool in statistics and social research, as it provides a rigorous framework for sample selection and data interpretation.
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