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.
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It is important to make sure your random sample is random in order to make sure the results are accurate, and to prevent experimenter bias.
Experiment cannot be predicted in advance is RANDOM EXPERIMENT...... set of all possible outcomes. outcome that can be predicted with certainity. when an experiment performed repeatedly- called trial. Ex. If a coin is tossed,we can't say,whetefr head or tail will appear .so it is a Random Experiment. Sample Space:-- Possible outcomes of a random experiment.. set of all posssible outcomes.. denoted by--- "S". and no. of elements is denoted by n(s). ex. In throwing a dice ,the number that appears at top is any one of 1,2,3,4,5,6 ,So here: S= 1,2,3,4,5,6 n(s) --- 6
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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