Difference between “Random, Stratified and Biased Sampling Methods of Data Collection are described below:
1. Random Sampling:
Word ‘random ‘ is a technical term in statistics pertaining to the method of sampling. If the data are so selected that every item in the group has equal chance of being selected, the method is called random sampling.
The data so collected are truly ‘Representative’ of the group. This method is very commonly restored in any draw of lottery. This is also the most widely used method in case of opinion polls.
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2. Stratified Sampling:
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The society is divided in so many strata – eco- normally or intellectually. So, a person picked randomly for interview may not represent the views of the stratum he does not belong to and data collected may not be ‘representative’. Hence, the group is divided into clearly identifiable strata and samples are selected from each strata randomly. But, this method requires considerable skill.
3. Biased Sampling:
If the selection is made with some inclination for a particular item, the method is called biased sampling. But, the choice may differ from the selector to selector, and hence, the interpretation, too. Hence, this method is used for high -end researches by the experts of the field.
On the whole, random data are considered most scientific, and hence, most widely restored to.
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The information sought may be gathered by- the questionnaire method, the interviewer method and the method of direct observation.
In economic and social enquires, information is almost always collected by having someone to fill up a form or questionnaires, But, a matter to be decided is whether the forms should be completed by any enumerator or investigators who collects data by asking questions and noting down answers or whether there should be left with the respondent to be filled up on his own. In the questionnaire method, each informant is provided with a questionnaire and is asked to supply the information in the form of answers to the questions.
Obviously, the method can be effective only when the informants have attained a certain level of education. It can work, for instance, when daily newspaper decides to conduct an opinion poll among its readers on some topical issue. But, the daily newspaper may not be read equally widely among all classes of people, and hence, may reflect the opinion of certain class of people only.
Thus the data collection may not be taken as totally ‘unbiased’ and ‘representative’. The drawback of the questionnaire method is that informants may not evince sufficient interest in the enquire even if they are sufficiently enlightened. Consequently, the data may involve a high percentage of non -response, and thus, fail to reflect the true state of the field of enquiry.
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In the interviewer method, enumerators go from one informant to another and elicit the required information. This method is used in population censuses. Also, it is the method that has to be employed in case the informants are not all literate or even if literate, have not attained the requisite educational level. For instance, if one is interested in family income and expenditure on different items, one may arrange to interview the head of each family and collect the information sought from him. But, this method is costly one as it needs trained manpower for the survey.
In the method of direct observation, the enquirer or his assistants get the data directly from the field of enquiry without having to depend on the co-operation of informants. When data are needed on the height and weight of, say, 100 college students, they will be approached individually and the height of each will be measured with a tape and the weight will be measured with a weighting balance.