When is random sampling used

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It involves a two-step process where two variables can be used to filter information from the population. It can easily be administered and helps in quick comparison. List of Partners vendors. Simple random sampling is a method used to cull a smaller sample size from a larger population and use it to research and make generalizations about the larger group.

It is one of several methods statisticians and researchers use to extract a sample from a larger population; other methods include stratified random sampling and probability sampling. The advantages of a simple random sample include its ease of use and its accurate representation of the larger population. Researchers generate a simple random sample by obtaining an exhaustive list of a larger population and then selecting, at random, a certain number of individuals to comprise the sample.

With a simple random sample, every member of the larger population has an equal chance of being selected. Researchers have two ways to generate a simple random sample. One is a manual lottery method. Each member of the larger population group is assigned a number. Next, numbers are drawn at random to comprise the sample group. The manual lottery method works well for smaller populations, but it isn't feasible for larger ones. In these situations, researchers prefer computer-generated selection.

It works via the same principle, but a sophisticated computer system, rather than a human being, assigns numbers and selects them at random. With a simple random sample, there has to be room for error represented by a plus and minus variance. For example, if in that same high school, a survey were to be taken to determine how many students are left-handed, random sampling can determine that eight out of the sampled are left-handed.

The same is true regardless of the subject matter. A survey on the percentage of the student population that has green eyes or is physically incapacitated would result in a high mathematical probability based on a simple random survey, but always with a plus or minus variance.

Simple random sample advantages include ease of use and accuracy of representation. No easier method exists to extract a research sample from a larger population than simple random sampling. There is no need to divide the population into sub-populations or take any steps further than plucking the number of research subjects needed at random from the larger group. Again, the only requirements are that randomness governs the selection process and that each member of the larger population has an equal probability of selection.

Selecting subjects completely at random from the larger population also yields a sample that is representative of the group being studied. This should help you put the study in perspective. Ever wonder what your personality type means?

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