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In order to do a systemic random sample, the items or individuals in the population are arranged in a certain way (for example, alphabetically). A random starting point is selected and then every __th (for example: 10th or 15th) individual is selected for the sample.
In math, a biased example could be when, someone asks only males to answer "do you like this product." its when the people chosen to answer the survey/sample is not random
With random sampling, you are hoping to get a representative sample of a whole, however statistically you could get a sample that is very different from the whole it was selected from. The larger the sample proportion of the whole, the better your sample will be. For example, a sample of 10 out of 100 is not as good as 20 out of 100. The bigger the sample the closer to the actual whole average you will get.
A random distribution is a random sample set displayed in the form of a bell curve. See random sample set.
to select a random sample you pick them at random