Random sampling
A benefit of using random sampling in a survey is the fact that it is the best way to ensure results are unbiased since the subjects are completely random.
An example of random sampling would be a group fifty students chosen out of a hat from a university of three-hundred students, the population would be all three-hundred students and the sample would be random because each student has an equal chance of being chosen.
Usually a computer programme would be used to draw a random selection from the population, however a more primitive method of assigning numbers would be to manually draw subjects or numbers from a ‘hat’ by the researcher, although this would only be done when dealing with smaller populations. For larger populations that have many members the computer method is preferred.
Random number tables known as number generators can also be used which selects a sample at an interval generated randomly. Random sampling relies on having complete lists of all the population in question, this list must be kept up to date and is often not available for larger population sizes (other techniques are better suited for large populations). Random sampling is more likely to be used when the researcher knows a limited amount about the population. Sample error can occur if the sample doesn’t end up accurately reflecting the population it is thought to represent.
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