COLLECTION OF PRIMARY AND SECONDARY DATA - THE NICONOMICS (2022)

Collection of primary and secondary data explained.

What is Statistical Inquiry ? Inquiry means a search for truth, knowledge or information. Thus, statistical enquiry means statistical investigation; one who conducts this type of inquiry is called an investigator. The investigators needs the help of certain persons to collect information, they are known as enumeratores, and repondents are those from whom the statistical information is collected.

SOURCES OF DATA

There are different sources of collection of data. Following are the various sources of collection of data.

SOURCES OF DATA

(A) Internal Sources

(B) External Sources

  • Primary Data
  • Secondary Data

Internal Sources

Q. Explain Internal sources of data with E.g..

Ans. 1. Different organisations and Government department generate the data as their regular function which is the internal information.

  • Internal data may be available in the organisation about sales, production, interest, profit, dividends etc.
  • Such data are complied and used for future planning.

Q. External sources of data with E.g..

Information collected from outside (other) organisations and institutions is called external data.

External data can be obtained from primary source or secondary source.

PRIMARY AND SECONDARY DATA

Primary data is original and first hand information and secondary data is collected through other sources. Primary data is first hand information for a particular statistical enquiry while the same data is second hand information for an another enquiry.

METHODS OF COLLECTING PRIMARY DATA

A. Personal Interviews

(a) Direct personal interview

According to this method, data are collected by the investigator personally from persons who are the subject to enquiry. He interviews personally every one who is in a position of supply information he requires. We can use this method of collection of data when area of enquiry is limited or when a maximum degree of accuracy is needed. The investigator must be skilled, tactful, accurate, pleasing and should not be biased.

Merits

  1. Original data are collected by this method.
  2. There is uniformity in collection of data.
  3. The required information can be properly obtained.
  4. There is flexibility in the enquiry as the investigator is personally present.
  5. Information can be obtained easily from the informants due to a personal interview.
  6. Since the enquiry is intensive and in person the result obtained are normally reliable and accurate.
  7. Informants relations to questions can be properly studied.
  8. Investigators can use the language of communication according to the educational standard of the information.

Limitations

  1. This method can be used if the field of enquiry is small. It cannot be used when field of enquiry is wide.
  2. It is costly method and consume more time.
  3. Personal bias can give wrong results.
  4. Investigators need to be trained and supervised for the job, otherwise results obtained may not be reliable.
  5. This method is lengthy and complex.

b. Indirect Personal Interview

Direct personal enquiry cannot be used in the case of the refusal and reluctance of the persons who are to be interviewed. Then an indirect personal enquiry can be conducted to get necessary information from an indirect source. Persons who have the knowledge of relevant material or event are interviewed and asked questions for collecting the data.

In indirect personal enquiry information is gathered by interviewing friends, neighbors, employers, relatives etc.

In this method a precaution is necessary in selecting the informants.

An informant should be a person :

  1. Who is not biased or prejudiced
  2. Must know the facts of problem
  3. Must be capable of answering correctly for giving true information,
  4. Is not motivated to give color to the fact.

To get success of collecting of data by this method, it is necessary that the evidence of one person alone is not to be relied upon; the opinions of various persons should be obtained to find out the real and true picture of the situation.

Merits

  1. This method covers a wide area of investigation. whenever the informant in direct investigation is reluctant to give information, or cannot be contacted, this method is a good alternative.
  2. As the information is obtained from the third party, it is more or less free from biased or prejudiced approach of the investigator and the informant.
  3. It saves labor, time and money.
  4. As the information covers a wide range, different aspects of problems can properly be studied.

Limitations

  1. As the information is obtained from the third-party and not by the person directly concerned, there exists as possibility of not getting true information.
  2. Various evidences obtained may be sometimes manipulated according to the interest of the person answering the question or supplying the information.

Difference between Direct Personal Investigation and Indirect Oral Investigation

1.Coverage This method is suitableThis method is suitable for
for smaller areas.Wider areas.
2. Originality The data collected are original in nature This method lacks originality as witnesses provide information.
3. CostIt is more costlier inIt is less costlier in terms of time, money and efforts.
4. Realiability This Method is More Reliable as as information is collected directly from is collected from the the informants. witnesses. This Method is less reliable

c. Information from correspondents

In this method, local agents or correspondent are appointed in the different parts of the investigation area. These agents regularly supply the information to the central office or investigator. They collect the information according to their own judgements and own methods. Radio and newspaper agencies generally obtain information by this method. It is also adopted by government departments. It is suitable when the information is to be obtained from a wide area and where a high degree of accuracy is not required.

Merits

  1. This method is comparatively cheap.
  2. It give results easily and promptly.
  3. It can cover a wide area under investigation.

Limitations

  1. In this method original data is not obtained.
  2. It gives approximate and rough results.
  3. As the correspondent use his own judgement, his personal bias may affect the accuracy of the information sent.
  4. Different attitude of different correspondents and agents may increase errors.

(B) Information through Questionnaires and Schedules:

(a) Mailed questionnaires

A list of questions relating to inquiry, which is called schedule or questionnaire, is prepared. This list of questions provides a space for each answer. Schedules are sent to informants by post, with a request to answer and return it within a specific time. Such schedules generally have prepared postage stamp affixed to them. If necessary, an assurance is given that the answer will be kept confidential. The success of this method depends on the cooperation that the informant is prepared to extend and the manner in which the questionnaire is drafter.

Merits

  1. Large field can be studied by this method.
  2. This is not an expensive method. It is cheap as mailing cost is less than the cost of personal visits.
  3. We can obtain original data by this method.
  4. It is free from the bias of the investigator as the information is given by the informants themselves.

Limitations

  1. It is difficult to presume the cooperation on the part of the informatnts.
  2. They may fail to send back the schedules or may misinterpret or may not understand some questions.Schedules sent back by the informants may be incomplete or inaccurate and it may be difficult to verufy the accuracy.
  3. There may be delays in getting replies to the questionnaires.
  4. This method can be used only when the informants are educated or literate, so that they return the questionnaries duly read, understood, answered.
  5. There is a possibility of getting wrong results due to partial responses, and those who do answer may not include certain type of persons from whom the specific information is required.

Suitability

(a) When it is compulsory by law to fill the questionnaire, e.g., government agencies compel bank and companies etc., to supply information regularly to the government in a prescribed from.

(b) This method can be successful when the informants are educated. Following are some suggestions for making this method more effective and successful.

(c) Questions should be simple and easy so that the informants may not find it a burden to answer them.

(d) Informants should not be required to spend for posting the questionnaires back therefore, prepaid postage stamp should be affixed.

(e) This method should be used in a large sample or wide universe.

(f) This method is preferred in such enquiries where it is compulsory by law to fill the schedule. Thus, there is little risk of non-response.

(g) The language of the schedule should be polite and should not hurt the sentiments of the informants.

Also Read – Stages of Statistical Studies

(b) Questionnaire to be filled by enumerators

Mailed questionnaire method poses a number of difficlties in collection of data. Generally, these filled questionnaries received are incomplete, inadequate and unrepresentative.

The second alternative approach is to send trained investigators or investigator to informants with standardized questionnaire which are to be filled in by the investigators. The investigator helps the informants in recording their answers. The investigators should be honest, tactful and painstaking. This is the most common method used by research organizations. They train with different persons tactfully, to get proper answers to the questions put to them. The statistical information collected under this method is highly reliable.

Merits

  • It can cover a wide area.
  • The results are not affected by personal bias.
  • True and reliable answer to dificult questions can be obtained through establishment of personal contact between the enumerator and informant.
  • As the infromation is collected by trained and experienced enumerators, it is reasonably accurate and reliable.
  • This method can be adopted in those cases also where the informants are illiterate.
  • Personal presence of investigator assured complete response and respondents can be persuaded to give the answers to the questionnaire.

Limitations

  • It is an expensive method as compared to other methods of primary collection of data, as the enumerators are required to be paid.
  • This method is time consuming since the enumerator is required to visit people spread out over a wide area.
  • This method need the supervision of investigators and enumerators.
  • Enmuerators need to be trained. Without good interview and proper training, most of the collected information is vague and may lead to wrong conclusions.
  • It needs a crmy of investigation to cover the wide area of universe and therefore it can be used by bigger organisations.

DRAFTING THE QUESTIONNAIRE

Following are the basic principles of drafting questionnaire :

  1. Covering Letters

The peron conducting the survey must introduce himself and make the aims of the objective of the enquiry clear to the informant. A personal letter can be enclosed indicating the purposes and aims of enquiry. The informant should be taken into confidence. A self – addressed and stamped envelope should be enclosed for the convenience of the informant to return the questionnaire.

  • Number of Questions

Minimum number of questions based on the objectives and scope of enquiry should be asked.

Therefore, normally fifteen to twenty – five questions should be asked. Lenghty questions should preferably be divided into parts. Irrelevant questions should be eliminated.

  • Personal questions should be avoided

The informant may not desire to answer such questions which may disclose his confidential, private or personal information. Questions affecting the sentiments of informants should not be asked.

  • The questions should be simple and clear

The language of the questions should be easy to understand.

  • The questions should be arranged logically

It helps in classification and tabulation of data. It is not logical to ask a man his income before asking him whether he is employed or not. There should be a proper sequence of the questions.

  • Instructions and Informations

Definite instructions for filling in the questionnaire should be given.

  1. The questions may be divided and sub

Divided under different heads and subheads and should be properly numbered for the convience of the informant and the investgator.

  • Multiple Choice Questions

Questions should be capable of objective answers. For this the informant should be able to give the answers simply by using a tick – mark in the blank space.

  • Simple Alternative Question (Yes/No)

As far as possible the questions should be framed in such a way that they are answered in ‘Yes’ or ‘No’ or ‘Right’ or ‘Wrong’.

  • Open Question

It makes the informant free to give any reply he chooses. Such questions should be minimum in number in the questionnaire.

  • The questions should be directly related to the point under enquiry for which the data is being collected.
  • Avoidance of leading questions

As far as possible leading questions should be avoided. Why do you like ‘Broke Bond Tea’ ? Instead of such simle question, two questions can be framed for enquiry, namely :

a. Which brand of tea do you take ?

b.Why do you prefer it ?

  • Attractive layout

The questionnaire should be made to look as attractive as possible. Keeping in view the possible answer the questions of schedule, sufficient space should be provided.

  • Avoidance of questions of calculations

As far as possible no question should be asked which require mathematical calculations like percentage, ratio etc. it gives strain to the informant and he may avoid sending the questionnaire back.

  • Cross Check

Some questions should provide the mean of checking inaccuracies in the answers.

For example, question on age and date of birth is a cross check. It helps to decide whether the informant is answering the questions correctly and consistently.

  • Questions on familiar topics

Questions which require strain should be avoided. Too much reliance on memories of distant past may elict wrong answers. Informants should be able to answer from their own memory and knowledge.

  • Pre – testing of questionnaire

Before taking the enquiry on a large scale the questionnaire drafted should be pre – tested with a small number of a group of persons.

COLLECTION OF SECONDARY DATA

Secondary data are those which are collected by some other agency and are used for further studies. It saves cost and time which is involved in collection of primary data. Secondary data may be either (a) published or (b) unpublished.

Published Sources

  • Government Publications

Different ministries and departments of Central and State Governments publish regularly current information along with statistical data on a number of subjects.

This information is quite reliable for related studies. The example of such publications are : Annual Survey of Industries, LAbour Gazette, Agriculture Statistics of India, Indian Trade Journal, etc.

  • Pulications of International organisations

We can obtain valuable international statistics from official publication of different international organisations, like, (U.N.O.), (I.L.O), (I.M.F)

  • Semi Official Publication

Official publications. Local bodies such as Muncipal Corporations, District Boards etc. publish periodical reports which give factual information about health, sanitation, births, deaths etc.

  • Reports of Committees and Commissions

Various Committees and Commissions are appointed by the Central and State Governments for some special study and recommendations. The report of such committes and commissions contain valuable data.

  • Private Publications
    • Journals and Newspapers : Journals like Eastern Economists, Journals of Industry and Trade, Monthly Statistics of Trade ; and newspapers, like Financial Express, Economic Times, collect and regularly publish the data on different fields of economics, commerce and trade.
    • Research Institutions : There are a number of institutions doing research on allied subjects.
    • Proffesional Trade Bodies : Institute of Chartered Accountants, Sugar Mills Association, Bombay Mill Owners Association, Stock Exchanges, Bank and Cooperative Socieities, Trade Unions, etc. publish statistical data.
    • Annual report of joint stock companies are also useful for obtaining statistical information. These are published by comapnies every year.
    • Articles, market review and reports also provide valuable data for research study.

Unpublished Data

Research institutions, trade associations, universities, labour bureaus, Research workers and scholars do collect data but they normally do not publish it. A part from the above sources we can get the information from records and files of Government and Private Offices.

Limitations of Secondary Data

  1. They may not have been collected by proper procedure.
  2. They may not be suitable for a required purpose. The information which was collected on a particular base may not be suitable and relevant to an enquiry.
  3. They may have been influenced by the biased Investigation or personal prejudices.
  4. They may be out of date and not suitable to the present period.
  5. They may not satisfy a reasonable standard of accuracy.
  6. They may not cover the full lertour of Investgation.

Precautions in the Use of Secondary Data

The investigator should consider the following points before using the secondary data :

  1. Are the data reliable ?
  2. Are the data suitable for the purpose of investigation ?
  3. Are the data adequate ?
  4. Are the data collected from proper method ?
  5. From which source were the data collected ?
  6. Who has collected the data ?
  7. Are the data biased ?

Thus, the secondary data should not be used at its face value. It is risky to use such statistics collected by others unless they have been properly scrutinised and found reliable, suitable and adequate.

COLLECTION OF PRIMARY AND SECONDARY DATA - THE NICONOMICS (1)
COLLECTION OF PRIMARY AND SECONDARY DATA - THE NICONOMICS (2)
COLLECTION OF PRIMARY AND SECONDARY DATA - THE NICONOMICS (3)
  • litera etc. Census data is interpreted and analysed to understand many economic and social issues in India.
  • The NSSO was established by the Government of India to conduct nationwide surveys on socio-economic issues. The data collected by NSSO are released through reports arid its quarterly journal ‘Sarvekshana’. NSSO provides periodic estimates of literacy, school enrolment, unemployment etc.

NSSO conducts three types of surveys :

  • Socio-economic surveys
    • Annual survey of industries
    • Agricultural surveys

NSSO conducts the following functions :

  • Carries out socioeconomic surveys
    • Collects data on price level in rural and( urban sector • Follows up surveys of economic census
    • Designs research activities.

Q. How primary data is collected ?

Ans. The most popular and common method is questionnaire/ interview schedule to collect the primary data. The questionnaire is managed by the enumerator, researchers, or trained investigators.

Q. What is basic difference between primary and secondary data.

Ans. Primary data is original and first-hand information collected originally while secondary data is collected through other sources like published reports, website, Government or company departments, etc.

Q. Write any five principles of drafting questionnaire.

Ans. Principles: {a) covering letter, (b) question should be simple and clear, (c) multiple choice questions, {d) minimum number of questions, (e) avoidance of questions of calculations.

Q. Distinguish between population and sample.

Ans. Population or Universe means the inclusion of all the items in the field of statistical equiry and sample means selection of few items as representatives of all the items.

Q. Name two methods of obtaining the simple random sample.

Ans. (a) Lottery method,

Sample Survey

In a sample survey information is collected about a part of the universe and on the basis result and conclusions are drawn about the whole universe or the part of the universe about which contains all the broad characteristics of the universe.

A sample survey is generally preferred where the size of population is large, where pop, is infinite, where different units of the universe are broadly similar and where very high degree of accuracy is not required.

Suitability

Survey is more appropriate than census survey. These days, sample survey is more popular so much so that even the accuracy of census survey is tested with a sample survey

CENSUS AND SAMPLING

  1. Population

Population or universe in statistics mean the inclusion of all the items in the field of statistical enquiry

Sampling

It means selection of few items as representative of all the item. Apart of whole population is called sample and the process is turned as sampling.

  • Census Method

A survey which includes every element of the population is known as Census Method. It is also known as the ‘Method of Complete Enumeration’ or ‘100% Enumeration’.

The essential feature of this method is that it covers every individual unit in the entire population. For example, if certain agencies are interested in studying the total population in India, they, have to obtain information from the household in rural and urban India.

Example : CENSUS OF INDIA, which is carried out every ten years includes a house-to-house enquiry covering all the households in India. Demosgraphic data on birth and death rates, literacy, published by the Registrar General of India. The last Census of India was held in February, 2011.

Suitability

Census method is suitable when :

  • size of population is small.
  • extensive study of diverse items is required.
  • high degree of accuracy is needed.
  • selection of sample items from universe is not possible. (v) reliable data is required.

Merits

  • Accurate and reliable data

Since under this method the information relating to each unit of the universe is collected.

  • Less element of bias

Since, information collected about each unit the possibility personal element or bias is minimum.

  • Comprehensive information

This method facilitates the collection wide and comprehensive information.

  • Appropriations

For certain types of surveys this method is more appropriate such as pop. census.

  • Characteristics of Universe

It contains all the characteristics of a universe.

Demerits

  1. Costly

It is a costly method.

  • Time consuming

This method involves more time and labour.

  • Unusable

This method cannot be used in many situations. For e.g., it cannot be used where universe is finite or where unis may finish during the process of testing. e.g., perishable commodities.

  • Unverifiable

In case any problem arises it is difficult to verify the inf. because. A census survey can nto be easily reconducted.

  • Huge Organisazation

A very large organization is needed for successfully conducting a census survey.

  • Unit for infinite universe

This method cannot be used in cases of infinite universe. In such a situaton it is not feasible to contact all the units of a universe.

Sample Survey

In a sample survey information is collected about a part of the universe and on the basis result and conclusions are drawn about the whole universe or the part of the universe about which contains all the broad characteristics of the universe.

A sample survey is generally preferred where the size of population is large, where pop, is infinite, where different units of the universe are broadly similar and where very high degree of accuracy is not required.

Suitability

  • size of the universe is very large.
  • when more accuracy is not required (iii) when an extensive study is not necessary.
  • when different items of the population are broadly similar.
  • when census method is not applicable.

Merits

  1. Economical : It saves time, money and labour.
  2. If sample can be taken out properly with due care and caution, it’s conclusion, and inferences can also be reliable and accurate like that of census survey.
  3. Scientific : This method is more appropritate for survey whose scope or area is very wide.
  4. Quick results : Results can be obtained very quickly with the help of this method.
  5. Even a small organization can use sampling method.

Demertis

  1. Under this method data are not very accurate.
  2. If a sample is not representative then all conclusion become wrong.
  3. For the proper selection of sample, special knowledge and understanding is required.
  4. This method is of no use for such surveys where information about the whole universe is required such as pop. census.

Q Which method is Better ?

Sampling method is genrally regarded better and more appropriate in comparison to census method because of the following reasons.

  1. This method is more appropriate because it involves less time and labor.
  2. This method is more appropriate for such data about which inf. is regularly available such as information about newly born babies.
  3. In many cases method is not possible. Keeping in view the above facts, generally the sample survey is more appropriate than census survey. These days, sample survey is popular so much that even the accuracy of census survey is tested with a sample survey. Keeping this in view the above facts, generally the sample.
  4. survey is more appropriate than census survey. These days, sample survey is more popular so much so that even the accuracy of census survey is tested with a sample survey.

METHODS OF SAMPLING

Broadly speaking, various methods of sampling can be grouped under two main heads:

(a) Random Sampling, and (b) Non-Random Sampling.

Let us discuss now the various sampling methods which are popularly used in practice.

METHODS OF SAMPLING

Random Sampling Non-Random Sampling

(a) Simple or UnrestrictedRandom Sampling (a) Judgement Sampling

(b) Restricted Random Sampling (b)Quota Sampling

  • Stratified Sampling
  • Systematic Sampling (c) Convenience Sampling or Quasi-Random Sampling
  • Cluster Sampling or Multi-stage Sampling

RANDOM SAMPLING

Random Sampling is one where the individual units (samples) are selected at random. It is called as probability sampling.

Random sampling does not mean unsystematic selection of units. It means the chances of each item of the universe being included in the sample is equal.

Following are the methods of random sampling.

Simple or Unrestricted Random Sampling

This method is also known as simple random sampling. In this method the selection of item is not determined by the investigator but the process used to select the terms of the sample decides the chances of selection. Each item of the universe has an equal chance of being included in the sample It is free from discrimination and human judgement. It depends on the law of probability which decides the inclusion of items in a sample. There are two methods of obtaining the simple random sample They are :

  • Lottery Method, and
  • Table of Random

Lottery Method : All the items of the universe are numbered and these numbers are written on identical pieces of paper (slip). They are mixed in a bowl and then there starts the

  • selection by draw one by one by shaking the bowl before every draw. The numbers are picked out blind folded. All silps must be identical in size, shape and colour to avoid the biased selection.

A special kind of rotating drum is used for Ending random numbers. It is called the Electronic Random Numbers Indicator Equipment. On which numbers 0 to 9 are written. The drum is rotated by a mechanical device and each time one piece comes out. The process is repeated to get the fill number of digits.

  • Table of random numbers : A table of random digits is simply a table of digits which have been generated by a random process. The following tables of random digits are available :
    • Tippett’s Random Sampling Numbers. There are 10400 numbers arranged 4 digits a time.
    • Rand Corporation’s a million random digits. (c) Fisher and Yates Table having 15000 digits.

Tippett’s table of random numbers is most popular which can be used in taking out sample. The first thirty sets of numbers out of 10400 are given below :

Suppose, we want to decide the sample of 15 students out of 2000 students in a college. We will first number all 2000 students from 1 to 2000. After numbering the students, now we will consult a page of Tigpett Table. We can get sample by taking any 15 successive number either horizontally or vertically.

Merits :

  1. It is more scientific method of taking; out samples from a universe . Every item in the universe has equal chance of being selected.
  2. It is more representative. When size of sample increases, it is more representative of the population as the Law of Inertia of large numbers and the Law of Statistical Regularity begin to operate.
  3. This method is economical as it saves sum, money and labor in investigating a population.
  4. The theory of probability is applicable, if the sample is random.
  5. Sampling error can be measured.

Demerits

  1. This requires complete lisp of population but up-to-date lists are not available in many enquiries.
  1. If the size of the sample is .small, then it will not be a representative of a population.
  2. When the distribution between items is very large, this method cannot be used.

Restricted Random Sampling They are as follows :

(i) Sratified random sampling : In this method the universe is divided into strata or homogeneous groups and an equal sample is drawn from each stratum. For example, suppose we want to know how much pocket money an average university student

gets every month will be taken equal sample from various strata, namely, BA. students, M.A. students and Ph.D. students, etc.

There are different types of stratified sampling :

  • Proportional stratified sampling is one in which the items are taken, from each stratum in the proportion of the units or the stratum to the total population;
  • Disproportionate stratified sampling is one in which units in equal numbers are taken from each stratum irrespective of its size.
  • Stratified weighted sampling is one where units are taken in equal number from each stratum, but weights are given to different strata on the basis of their size.

Merits

The sample taken under this method is more representative of the universe as it has been taken from different groups of universe

It ensures greater accuracy as each group (stratum) is so formed that it consists of uniform or homogeneous items.

It is easy to administer as universe is sub-divided.

For non-homogeneous population, it is more reliable.

Demerits

  1. Stratified sampling is not possible unless some information concerning the population and its strata is available.
  2. It proper stratification is not done the sample will have an effect of bias

(ii) Systematic sampling or quasi-random sampling : This is used when a complete list of the population is available. This is called a quasi-random method because a kind of randomness is achieved by preparing this list in some random order, for example, alphabetical order.

The method consists of selecting every nth item from the list, n stands for any number. Suppose We have a universe of 10,000 items and We Want a sample of 1000, then we take n = 10. The method of selecting the first item from the list is to decide at random from the first sampling interval, i.e., between one and

ten.

Suppose we pick up the 5th item. Then the other items will be

15th, 25th, 35th, and so on until we have got our full sample.

Merits

  1. It is systematic, very simple, convenient and checking can also be done quickly.
  2. In this method time and work is reduced much.
  3. The results are also found to be generally satisfactory.

Demerits

  1. Systematic selection may or may not approach chance or random selection as random will not be a determining factor in the selection of a sample.
  2. It is feasible only if the units are systematically managed.
  3. The universe is arranged in wrong manner, the results will be misleading.

(iii) Cluster sampling or multi-stage sampling : In this method Sampling is carried out in a number of stages. This is done when we know that for getting reliable results we have to divide and sub-divide a universe according to its characteristics. Thus, if a survey is to be conducted in a country it will first be divided into zones or states or regions, then into smaller units cities, towns and villages and then into localities and households. At each stage sampling is done by a suitable method, say simple random sampling. This method of sampling is very helpful in many large scale survey where the preparation of the list of all units in the population is difficult, time consuming and expensive.

Non-Random Sampling

It is done on the basis of convenience and judgement of the investigator and not on the basis of probility. The following are imp. methods.

  1. Deliberate Sampling or Purpositive or Judgement Samplery This method is also called judgement sampling. According to this method, for selecting a sample, no specific procedure is used rather the investigator according to his desire and needs select those units of the universe as sample which fully represents the Universe. Units which are to be included in the sample inclusively depends upon the discreation of the person who results the sample. For e.g., If he has to select a sample of 40 students out of 1000 students which 40 students will be selected absolutely depends upon the direction of peoples concern. In this method, there is every possibility that only those units may be included in the sample.

Merits

  1. This method is simple
  2. It involves less expenditure
  3. This method is more appropriate for such surveys where all the items of the Universe are similar.

Demerits

  1. This method contains an element bias.
  2. Data collected using this method is not reliable.

Quota Sampling

It is a kind of judgemetn sampling. According to this method.

  1. Universe or population is divided into various groups on the basis of different characters. Such as income, age or religion.
  2. Quota is fixed for each group such as, how many units are to be taken from income groups for sample.
  3. According to the prescribed Quota for various groups the investigation chosen by the unit according to his discretion. Under this method the sampling of units is different from that of Random sampling.

Convienience Sampling

This method is selected purely on the basis of convienience for e.g., for study the running away students from school the investigator may select a school or schools in the neighborhood because it is convienient him to go to the school.

Discuss the various qualities of Good Sample.

Essentials/Qualities of a Good Sample

For obtaining impartial and accurate results, a sample should have the following qualities :

  1. Representative. A good sample is one which represents the characteristics of all the items in the universe. This is possible only when each and every item in population has a fair and equal chance of being selected as a sample.
  2. Homogeneity. The items that are selected as samples should be homogeneous nature so that they can truly help in investigation. However, these samples should not be contradictory to each other.
  3. Independent. Selection of one item of the universe in the sample should not depend selection of some other item in the sample, e.g.., as done in systematic sampling. Items in the population should be independent of each other.
  4. Sufficiency. To get accurate and reliable conclusions, the number of items in the sample should be adequate enough to cover all characteristics of the universe.

Reliability of Sample Data

For ensuring reliability in sampling certain principles must be followed. In sampling method it is presumed that whatever conclusions are drawn from a sample are also true for the whole population. This presumption is based mainly on the following two laws :

  1. The Law of Statistical Regularity
  2. The Law of Inertia of Large Numbers. –
    • The Law of Statistical Regularity

The law of statistical regularity is derived from the mathematical theory of probability. It says that a comparatively small group of items chosen at random from a very large group will, on the average, represent the characteristics of the large group. In the process of sampling each unit of the universe has an equal chance of being selected. Therefore, the selected items can be said to be representative of the universe. Although the law is not as accurate as a

scientific law is, it does insure a reasonable degree of accuracy.

2. The Law of Inertia of Large Numbers

This law is also called the law of stability of mass data. It is based on the law of statistical regularity. Basically, it states that if the numbers involved are very large, the change in a sample is likely to be very small in other words, the individual units of a universe very continually but the total universe changes slowly. That is, large aggregates are most stable than small ohes. Because of the slow change in the nature of total universe this law is called the law of inertia (laziness) of large numbers.

For example, sugar production of factory will vary significantly from year to year but the sugar production of a country as a whole will remain comparatively stable. Or a great change may take place in the male-female ratio of family may appreriably change over a short period, but the male-female ratio of a country as a whole will remain almost for the period.

Statistical Errors

There is a great difference in the meaning of mistake and error in statistics. Mistake means a wrong calculation or use of inappropriate method in the collection or analysis of data. Error means “ the difference between the true value and the estimated value.” In other words the difference between the true approximated (estimated value) and the actual value (true value) is called statistical error in a technical sense. For example, we make an estimation that in a particular meeting , 1000 persons are there. But we count persons, it may be wrongly counted as 1,030. There is a difference of 30 between the estimated value and counted value. This difference is called ‘error’ in statistics. But when we make wrong calculation, following wrong method, draw wrong conclusions, etc. They are known as ‘mistake’. For example, there is a meeting, we sent a person to count the audience, he counts the number of persons as 600, but actually, there are 590 persons. This is called ‘mistake’ in counting.

Top Articles

You might also like

Latest Posts

Article information

Author: Laurine Ryan

Last Updated: 12/03/2022

Views: 6020

Rating: 4.7 / 5 (77 voted)

Reviews: 84% of readers found this page helpful

Author information

Name: Laurine Ryan

Birthday: 1994-12-23

Address: Suite 751 871 Lissette Throughway, West Kittie, NH 41603

Phone: +2366831109631

Job: Sales Producer

Hobby: Creative writing, Motor sports, Do it yourself, Skateboarding, Coffee roasting, Calligraphy, Stand-up comedy

Introduction: My name is Laurine Ryan, I am a adorable, fair, graceful, spotless, gorgeous, homely, cooperative person who loves writing and wants to share my knowledge and understanding with you.