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Census or Complete Enumeration. A survey, which includes every element of the population, is known as Census or the Method of Complete Enumeration. If certain agencies are interested in studying the total population in any country, they have to obtain information from all the households in rural and urban areas of a country. The essential feature of this method is that this covers every individual unit in the entire population. You cannot select some and leave out others.
Survey Population or the Universe in statistics means totality of the items under study. Thus, the Population or the Universe is a group to which the results of the study are intended to apply. A population is always all the individuals/items who possess certain characteristics (or a set of characteristics), according to the purpose of the survey. The first task in selecting a sample is to identify the population. Once the population is identified, the researcher selects a Representative Sample, as it is difficult to study the entire population. A sample refers to a group or section of the population from which information is to be obtained. A good sample (representative sample) is generally smaller than the population and is capable of providing reasonably accurate information about the population at a much lower cost and shorter time.
Suppose you want to study the average income of people in a certain region. According to the Census method, you would be required to find out the income of every individual in the region, add them up and divide by number of individuals to get the average income of people in the region. This method would require huge expenditure, as a large number of enumerators have to be employed. Alternatively, you select a representative sample, of a few individuals, from the region and find out their income.
The average income of the selected group of individuals is used as an estimate of average income of the individuals of the entire region.
Most of the surveys are sample surveys. These are preferred in statistics because of a number of reasons. A sample can provide reasonably reliable and accurate information at a lower cost and shorter time. As samples are smaller than population, more detailed information can be collected by conducting intensive enquiries. As we need a smaller team of enumerators, it is easier to train them and supervise their work more effectively.
There are two main types of sampling, random and nonrandom.
Random Sampling. As the name suggests, random sampling is one where the individual units from the population (samples) are selected at random. In the random sampling, every individual has an equal chance of being selected and the individuals who are selected are just like the ones who are not selected. This is also called lottery method.
Exit Polls. You must have seen that when an election takes place, the television networks provide election coverage. They also try to predict the results. This is done through exit polls, wherein a random sample of voters who exit the polling booths are asked whom they voted for. From the data of the sample of voters, the prediction is made.
Non-Random Sampling. There may be a situation that you have to select 10out of 100households in a locality. You have to decide which household to select and which to reject. You may select the households conveniently situated or the households known to you or your friend. In this case, you are using your judgement (bias) in selecting 10 households. This way of selecting 10out of 100households is not a random selection. In a non-random sampling method all the units of the population do not have an equal chance of being selected and convenience or judgement of the investigator plays an important role in selection of the sample. They are mainly selected on the basis of judgment, purpose, convenience or quota and are non-random samples.
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