Since the beginning of the twentieth century the economic and social life of the people and the functional system of industry and business, educational and medical facilities and other activities of the community have undergone substantial changes due to spectacular developments in the field of science and technology. Now the emphasis is on specialization in mass production and utilization of goods and services of a given type with a view to get the maximum possible benefit per unit of cost. Considerable planning is required in a large-scale projects and any rational decision regarding efficient formulation and execution of suitable plans and projects or an objective assessment of their effectiveness, whether in the field of industry, business or governmental activities, has necessarily to be based on objective data regarding resources and needs. There is, therefore, a need for various types of statistical (quantified) information to be collected and analyzed in an objective manner and presented suitably so as to serve as a sound basis for taking policy decisions in different fields of human activity. In modern times, the primary users of statistical data are the state, industry, business, scientific institutions, public organizations and international agencies.
For instance, to execute its various responsibilities, the state is in need of a variety of information regarding different sectors of the economy, sections of people and geographical regions in the country as well as information on the available resources such as manpower, cultivable land, forests, water, minerals and oil. If the resources were unlimited, planning would be relatively simple as it would consist in just providing each one with what he needs in terms of money, material, employment, education etc. But such a situation is only hypothetical, as in reality the resources are limited and the needs are usually not well defined and are elastic.
Therefore, for the purpose of proper planning fairly detailed data on the available resources and on the needs are to be collected. For example, the country is in need of data on production and consumption of different types of products to enable it to take objective decisions regarding its import and export polices. Statistical information on the cost of living of different categories of people living in various parts of the country is of importance in shaping its policies in respect of wage and price levels.
Complete enumeration survey
One way of obtaining the required information at regional and country level is to collect the data for each and every unit (person, household, field, factory, shop, etc as the case may be) belonging to the population or universe, which is the aggregate of all units of a given type under consideration and this procedure of obtaining information is termed complete enumeration survey. The effort, money and time required for carrying out complete enumeration surveys to obtain the different types of data will, generally, be extremely large. However, if the information is required for each and every unit in the domain of study, a complete enumeration survey is clearly necessary. Examples of such situations are income tax assessment where the income of each individual is assessed and taxed, preparation of voters’ list for election purposes and recruitment of personnel in an establishment etc. But there are many situations, where only summary figures are required for the domain of study as a whole or for group of units and in such situations collection of data for every unit is only a means to an end and not the end itself. It is worth mentioning that exact planning for the future is not possible, since this would need accurate information on the resources that would be available and on the needs that would have to be satisfied in future. In general, past data are used to forecast the resources and the needs of the future and hence there is some element of uncertainty in planning. Because of this uncertainty, only broad (and not exact) allocations of the resources are usually attempted. Thus some margin of error may be permitted in the data needed for planning, provided this error is not large enough to affect the broad allocations.
Considering that some margin of error is permissible in the data needed for practical purposes, an effective alternative to a complete enumeration survey can be a sample survey where only some of the units selected in a suitable manner from the population are surveyed and an inference is drawn about the population on the basis of observations made on the selected units. It can be easily seen that compared to a sample survey, a complete enumeration survey is time-consuming, expensive, has less scope in the sense of restricted subject coverage and is subject to greater coverage, observational and tabulation errors. In certain investigations, it may be essential to use specialized equipment or highly trained field staff for data collection making it almost impossible to carry out such investigations except on a sampling basis. Besides, in case of destructive surveys, a complete enumeration survey is just not practicable. Thus, if the interest is to obtain the average life of electric bulbs in a batch then one will have to confine the observations, of necessity, to a part (or a sample) of the population or universe and to infer about the population as a whole on the basis of the observations on the sample. However, since an inference is made about the whole from a part in a sample survey, the results are likely to be different from the population values and the differences would depend on the selected part or sample. Thus the information provided by a sample is subject to a kind of error which is known as sampling error. On the other hand, as only a part of the population is to be surveyed, there is greater scope for eliminating the ascertainment or observational errors by proper controls and by employing trained personnel than is possible in a complete enumeration survey. It is of interest to note that if a sample survey is carried out according to certain specified statistical principles, it is possible not only to estimate the value of the characteristic for the population as a whole on the basis of the sample data, but also to get a valid estimate of the sampling error of the estimate. There are various steps involved in the planning and execution of a sample survey. One of the principal steps in a sample survey relate to methods of data collection.