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Kerala Plus One Economics Notes Chapter 12 Collection of Data
Sources of Data
Statistical data can be obtained from two sources. The enumerator may collect the data by conducting an inquiry or an investigation. Such data are called Primary Data, as they are based on first-hand information.
If the data have been collected and processed by some other agency, they are called Secondary Data. Generally, the published data are secondary data.
Methods of Collecting Primary Data
There are three basic ways of collecting data:
- Personal Interviews
- Mailing (questionnaire) Surveys
- Telephone Interviews
1. Personal Interviews: This method is used when the researcher has access to all the members. The researcher conducts face to face interviews with the respondents. Personal contact is made between the respondent and the interviewer. The interviewer has the opportunity of explaining the study and answering any query of the respondents.
2. Mailing Questionnaire: When the data in a survey are collected by mail, the questionnaire is sent to each individual by mail with a request to complete and return it by a given date. The advantages of this method are that it is less expensive. It allows the researcher to have access to people in remote areas too, who might be difficult to reach in person or by telephone. It does not allow the influence of the respondents by the interviewer. It also permits the respondents to take sufficient time to give thoughtful answers to the questions.
3. Telephone Interviews: In a telephone interview, the investigator asks questions overthe telephone. The advantages of telephone interviews are that they are cheaper than personal interviews and can be conducted in a shorter time. They allow the researcher to assist the respondent by clarifying the questions. The telephone interview is better in the cases where the respondents are reluctant to answer certain questions in personal interviews.
Collection of Secondary Data
Secondary data are those which are available in published or unpublished records. Once a decision is taken to collect secondary data, the question of sources of data arises. There are two sources for the collection of secondary data, namely, published sources and unpublished sources.
Published Sources:
- Official publications of the central, state, and local governments.
- Official publications of international agencies like the United Nations Organization and its subsidiaries.
- Reports and publications of trade associations, chambers of commerce, banks, etc.
- Reports of committees and commissions.
- Reports published in technical trade journals.
- Reports submitted by researchers, economists, etc.
Unpublished Sources:
- Unpublished materials found with research institutes, trade associations, chamber of commerce, etc.
Census Survey and Sample Survey
Under census method, we collect information from each and every unit of population relating to the problem under investigation. On the other hand, the under-sample method, rather than collecting information about all the units of population, we collect information from a few selected items from the population.
Methods of Sampling
There are various methods of selecting samples from a population. These are called sampling techniques.
The two types of sampling techniques are random sampling and non-random sampling.
Random Sampling Methods
Random sampling is a technique of drawing a sample from the population in which each and every unit of the population has an equal chance of being included in the sample. It is further divided into simple random sampling and restricted random sampling.
a) Simple random sampling: In this method, the sample is taken from the population without making any division or classification of the population. Hence, every unit of the population has an equal chance of being selected in the sample. Simple random sampling may be done either by using lottery method or by Table of random numbers.
b) Restricted random sampling: Restricted random sampling is of mainly three types. Stratified sampling, systematic sampling and cluster sampling.
1. Stratified sampling: When the population is heterogeneous, stratified sampling method is used. Under this method the whole population is divided into various groups or strata of units, such that the units in each class possess similar characteristics. For example, suppose you are studying about the consumption pattern of students in your school. The population comprises the whole students studying in various standards of your school. A student studying in standard-5 and a student studying in standard-9 may have different consumption patterns. That is, for this characteristic, the population is heterogeneous. Hence, different standards can be selected as different groups or strata. Then sample is drawn from each stratum at random.
2. Systematic sampling: A systematic sampling is formed by selecting one at random and then selecting the rest at evenly spaced intervals until the sample size has been reached. Suppose that in the nature club of your school, there are 100 members and you want to make a core group of 10. First you number the 100 students of the club from 1 to 100. By lottery method or by random table method you select one student from the first ten. Let it be the 7th student. Then take an appropriate interval and select the rest 9 students. If the interval you had taken is 10, then the second student in the sample is the 17th student, the third student in the sample is the 27th student, etc.
3. Cluster sampling: This type of sampling is carried out in several stages. Suppose we are studying about the employment of households in Kerala. In the first stage, Kerala is divided into three or four zones. Then each zone is divided into districts. Then each district is divided into villages. From each district, sample of villages may be taken at random. From each selected village, households of required size are also taken at random. Since several stages involve in cluster sampling, it is also known as multi-stage sampling.
Non-Random Sampling
In this method of sampling the investigator himself makes the choice of sample from the population according to his own discretion which he thinks to be the best. Here, all the units in the population do not have equal chance of being selected in to the sample.
Sampling Errors and Non-Sampling Errors:
Sampling Errors
The purpose of the sample is to take an estimate of the population. Sam^g error refers to the differences between the sample estimate and the actual value of a characteristic of the population. It is the error that occurs when you make an observation from the sample taken from the population. Thus, the difference between the actual value of a parameter of the population and its estimate is the sampling error.
Non-Sampling Errors
Non-sampling errors are more serious than sampling errors because a sampling error can be minimized. But errors due to mistakes while framing tables and data entry will affect the final result. They are non-sampling errors.