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Random sampling usually provides a sample that is representative of a population because each member of the population is selected independently and has an equal chance, or probability, of being included in the study. (Grove, 2015, p. 37). It is important to conduct random sampling because it allows the study to be presented in the most unbiased form of data collection. Choosing factors at random and by chance provides a general understanding for what statistic is being collected. It limits and prejudice from the collectors, whether it is intentional or unintentional selections for the study. On the contrary, there are complications that may arise in random sampling. When sampling, there must be multiple trials in order to fully grasp a complete understanding that the statistics are accurate. Collecting one sample is only a snap shot of what is occurring at that one particular time. Multiple data collection trials should take place to guarantee the accuracy based on reoccurrence and the mean and mode of the elements in question. With random sampling, your data lacks a baseline to compare information because elements are nonspecific. To prevent from having an unsteady baseline for random sampling, some limitations must be put into play to ensure accuracy of the statistic. For example if you wanted to conduct a study about how often people wash their hands through out the day, maybe conduct the study among a certain occupation or hobby instead of generalizing the populatio

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