Principle Steps in Sample Survey

 THE PRINCIPAL STEPS IN A SAMPLE SURVEY

              The main steps involved in the planning and execution of a sample survey may be grouped somewhat arbitrarily under the following heads:

Objective of the Survey: The first step is to define in clear and concrete terms, the objectives of the survey. It is generally found that even the sponsoring agency is not quite clear in mind as to what it wants and how it is going to use the results. The sponsors of the survey should take care that these objectives are commensurate with the available resources in terms of money, manpower and the time limit required for the availability of the results of the survey.

Defining the Population to be Sampled: The Population, i.e., the aggregate of objects (animate or in-animate) from which sample is chosen should be defined in clear and unambiguous terms. For example, in sampling of farms clear-cut rules must be framed to define a farm regarding shape, size, etc., keeping in mind the border-line cases so as to enable the investigator to decide in the field without much hesitation whether or not to include a given farm in the population.

The Frame and Sampling Units: The Population must be capable of division into what are called sampling units for purpose of sample selection. The sampling units must cover the entire population and they must be distinct, unambiguous and non-overlapping in the sense that every element of the population belongs to one and only one sampling unit. For example, in socio-economic survey for selecting people in a town, the sampling unit might be an individual person, a family, a household or a block in a locality.

In order to cover the population decided upon, there should be some list, map or other acceptable material, called the frame, which serves as a guide to the population to be covered.

Data to be collected: The data should be collected keeping in view the objectives of the survey. The tendency should not be to collect too much data some of which are never subsequently examined and analysed. A practical method is to chalk out an outline of the tables that the survey should produce. This would help in eliminating the collection of irrelevant information and ensure that no essential data are omitted.

The Questionnaire or Schedule:  Having  decided about the type of the data to be collected, the next important part of the sample survey is the construction of the questionnaire (to be filled in by the respondent) or schedule of enquiry (to be completed by the interviewer) which requires skill, special technique as well as familiarity with the subject-matter under study. The questions should be clear, brief, corroborative, non-offending, courteous in tone, unambiguous and to the point so that not much scope of guessing is left on the part of the respondent or interviewer. Suitable and detailed instructions for filling up the questionnaire or schedule should also be prepared.

                            Sample Questionnaire

              

Method of Collecting Information: The two methods commonly employed for collecting data for human populations are:

(Ø) Interview Method: In this method, the investigator goes from house to house and interviews the individuals personally. He asks the questions one by one and fills up the schedule on the basis of the information supplied by the individuals.

          

Structured Interview Un-structured Interview                                                     

(Ø) Mailed Questionnaire Method: In this method, the questionnaire is mailed to the individuals who are required to fill it up and return it duly completed.

Non-respondents: Quite often (due to practical difficulties), the data cannot be collected for all the sampled units. For example, the selected respondent may not be available at his place when the investigator goes there or he may fail or even refuse to give certain information when contacted. This incompleteness, called non-response, obviously tends to change the results. Such cases of non-response should be handled with caution in order to draw unbiased and valid conclusions. Procedures will have to be devised to deal with those who do not furnish information. The reasons for non-response should be recorded by the investigator.

Selection of Proper Sampling Design: The size of the sample (n), the procedure of selection and the estimation of the population parameters along with their margins of uncertainty are some of the important statistical problems that should receive the most careful attention.

A number of designs (plans) for the selection of a sample are available and a judicious selection will guarantee good and reliable estimates. For each sampling plan, rough estimates of sample size n can be obtained for a desired degree of precision. The relative costs and time involved should also be considered before making a final selection of the sampling plan.

Organization of Field Work: It is absolutely essential that the personnel should be thoroughly trained in locating the sample units, recording the measurements, the methods of collection of required data before starting the field work. The success of a survey to a great extent depends upon the reliable field work. It is very necessary to make provisions for adequate supervisory staff for inspection after field work.

From a practical point of view a small pre-test, (i.e., trying out the questionnaire and field methods on a small scale) has been found to be immensely useful. It always helps to decide upon an effective method of asking questions and results in the improvement of the questionnaire.

Summary and Analysis of the Data: The analysis of the data may be broadly classified into the following heads:

Scrutiny and editing of the data: An initial quality check should be carried out by the supervisory staff while the investigators are in the field. Accordingly, the schedules should be thoroughly scrutinised to examine the plausibility and consistency of the data obtained. The scrutiny or editing of the completed questionnaires will help in amending recording errors or in eliminating data that are obviously erroneous and inconsistent.

Tabulation of data: Before carrying out the tabulation of the data, we must decide about the procedure for tabulation of the data which are incomplete due to non-response to certain items in the questionnaire and where certain questions are deleted in the editing process. The method of tabulation, viz., hand tabulation or machine tabulation, will depend upon the quantity of the data. For large-scale survey, machine tabulation will obviously be much quicker and economical. For a large-scale sample survey, the use of code numbers for qualitative variables is essential for machine tabulation. With simple questionnaires, the answers can sometimes be pre-coded, i.e., entered in a manner in which they can be conveniently or routinely transferred to mechanical equipment such as personal computers, etc. Finally, the tables that lead to the estimates are prepared.

 Statistical analysis: After the data has been properly scrutinised, edited and tabulated, a very careful statistical analysis is to be made. Different methods of estimation may be available for the same data. Appropriate formulae should then be used to provide final estimates of the required information. Efforts should be made to keep the procedure free from errors.

 Reporting and conclusions: Finally, a report incorporating detailed statements of the different stages of the survey should be prepared. In the presentation of the results, it is good practice to report the technical aspect of the design, viz., the types of the estimators used along with the amount of error to be expected in the most important estimate.

 Information gained for Future Surveys: Any completed survey is helpful in providing a note of caution and taking lessons form it for designing future surveys. The information gained from any completed sample in the form of the data regarding the means, standard deviations and the nature of the variability of the principal measurements tougher with the cost involved in obtaining the data serves as a potential guide for improved together sampling.

Sources: Fundamentals of Applied Statistics, S.C.Gupta & V.K.Kapoor, Fundamentals of Mathematical Statistics, S.C.Gupta & V.K.Kapoor, Sampling Techniques, W.G.Cochran