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There are circumstances when it is important and others when it is not. If, for example, you wanted a sample of all schools in the country, it would make more sense to go for cluster sampling. A lot of market research work will require quota sampling. So the supremacy of a random sample is a myth.
A random distribution is a random sample set displayed in the form of a bell curve. See random sample set.
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.
to select a random sample you pick them at random
besause it is cheaper and useful when time is limited