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. 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