 # Difference between Random Sampling and Non-random Sampling

There are mainly two methods of sampling which are random and non-random sampling. Random sampling is referred to as that sampling technique where the probability of choosing each sample is equal.

The sample that is chosen randomly is an unbiased representation of the total population. If at all, the sample chosen does not represent the population, it leads to sampling error.

Non-random sampling is a sampling technique where the sample selection is based on factors other than just random chance. In other words, non-random sampling is biased in nature.

Here, the sample will be selected based on the convenience, experience or judgment of the researcher.

Following are some of the points of difference between random sampling and non-random sampling

 Random Sampling Non-random Sampling Definition Random sampling is a sampling technique where each sample has an equal probability of getting selected Non-random sampling is a sampling technique where the sample selected will be based on factors such as convenience, judgement and experience of the researcher and not on probability Biases involved in Sampling Random sampling is unbiased in nature Non-random sampling is biased in nature Based on Based on probability Based on other factors such as convenience, judgement and experience of researcher but, not based on probability Representation of Population Random sampling is representative of the entire population Non-random sampling lacks the representation of the entire population Chances of Zero Probability Never Zero probability can occur Complexity Random sampling is the most simple sampling technique Non-random sampling method is a somewhat complex sampling technique

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