Random Sampling
A probability method in which every member of the population has a known, nonzero chance of selection, typically an equal chance.
Random sampling selects units from a sampling frame by chance, so that every member of the population has a known probability of being included. In simple random sampling, each member has an equal chance, often achieved with random number generation. Because selection does not depend on convenience or the researcher's judgment, random sampling reduces selection bias and is the foundation for inferential statistics, which assume that the sample can stand in for the population.
In a thesis, using random sampling justifies statistical generalization from sample to population, which is what tests, confidence intervals, and p-values presuppose. If you claim randomness, examiners will expect you to explain the frame and the selection procedure. If true random sampling was not feasible, it is better to name your actual method honestly and address its limits than to overstate your design.
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