Random and Nonrandom Samples

Depending on how a sample is drawn, it may be a random sample or a nonrandom sample. A random sample is a sample drawn in such a way that each member of the population has some chance of being selected in the sample. In a nonrandom sample, some members of the population may not have any chance of being selected in the sample. Suppose we have a list of 100 students and we want to select 10 of them. If we write the names of all 100 students on pieces of paper, put them in a hat, mix them, and then draw 10 names, the result will be a random sample of 10 students.

However, if we arrange the names of these 100 students alphabetically and pick the first 10 names, it will be a nonrandom sample because the students who are not among the first 10 have no chance of being selected in the sample. A random sample is usually a representative sample. Note that for a random sample, each member of the population may or may not have the same chance of being included in the sample. Two types of nonrandom samples are a convenience sample and a judgment sample. In a convenience sample, the most accessible members of the population are selected to obtain the results quickly.

For example, an opinion poll may be conducted in a few hours by collecting information from certain shoppers at a single shopping mall. In a judgment sample, the members are selected from the population based on the judgment and prior knowledge of an expert. Although such a sample may happen to be a representative sample, the chances of it being so are small. If the population is large, it is not an easy task to select a representative sample based on judgment. The so-called pseudo polls are examples of nonrepresentative samples.

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For instance, a survey conducted by a magazine that includes only its own readers does not usually involve a representative sample. Similarly, a poll conducted by a television station giving two separate telephone numbers for yes and no votes is not based on a representative sample. In these two examples, respondents will be only those people who read that magazine or watch that television station, who do not mind paying the postage or telephone charges, or who feel compelled to respond. Another kind of sample is the quota sample.

To draw such a sample, we divide the target population into different subpopulations based on certain characteristics. Then we select a subsample from each subpopulation in such a way that each subpopulation is represented in the sample in exactly the same proportion as in the target population. A quota sample based on a few factors will skew the results. A random sample (one that is not based on quotas) has a much better chance of being representative of the population of all voters than a quota sample based on a few factors.

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