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In the process of monitoring and evaluation of projects and programmes, the selection of a sample is one of the most significant stages that determines the accuracy, reliability, and validity of findings. Since it is not always feasible to study the entire population due to cost, time, and logistical constraints, evaluators often rely on a representative subset, known as a sample, to draw conclusions about the population. The process of selecting a sample involves a systematic approach based on principles of research methodology. Careful attention to sampling techniques ensures that the evaluation findings are both generalizable and useful for decision-making. Sampling in monitoring and evaluation is not merely a technical exercise but also a strategic activity that must align with the objectives, resources, and context of the project. The first step in the selection of a sample is defining the population. In monitoring and evaluation, the population refers to the entire group of individuals, households, institutions, or units that the project targets or that are relevant for assessment. For example, in an evaluation of an urban housing project, the population could include all beneficiaries, local authorities, and implementing agencies. A clear understanding of the population is crucial because ambiguity in defining who or what is included may lead to biased results. Evaluators need to ensure that the population is clearly bounded in terms of geography, time, and characteristics. Once the population is defined, the second step involves determining the sampling frame. The sampling frame is a list or database from which the sample is drawn. In practice, this might include a list of all registered beneficiaries of a programme, school registers in an education project, or hospital records in a health intervention. The accuracy of the sampling frame is vital, as an incomplete or outdated list can systematically exclude certain groups, thereby undermining representativeness. For example, in a poverty alleviation project, if the sampling frame excludes migrant workers who are not formally registered, the evaluation results may not reflect the true impact. The third step is to determine the sample size. Sample size is critical because it affects both the precision of estimates ___ _______ _____ _______ _________ _____ ________.
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