We collect data to know and understand the root cause of problems. So that we can give solutions to these problems. Lets understand by example--After many fluctuations the output of food grains rose to 132 million tonnes in 1978-79 from 108 million tonnes in 1970-71, but fell to 108 million tonnes in 1979-80. Production of food grains then rose continuously to 252 million tonnes in 2015-16 and touched 272 million tonnes in 2016–17.”
Now this whole information collected is called Data. Here values are varied every year, so these are called variables.
WHAT ARE THE SOURCES OF DATA?
There are two sources of data:
Primary data resourcing- The researcher may collect the data by conducting an enquiry. This data is based on first hand information or collected for the first time. Direct from target persons. Example : In a group of 100 people, the head of the group wants to know how many people are graduated or not. For this, the head of the group will have to enquire from all group members, by asking questions from them to collect the desired information. The data you get, is an example of primary data.
Secondary Data resourcing- If the data already have been collected and processed (scrutinised and tabulated) by some other agency and its taken from them. They can be obtained either from published sources such as government reports, documents, newspapers, books written by economists or from any other source, for example, a website.
HOW DO WE COLLECT THE DATA?
Data is collected by doing surveys. Survey is a method of gathering information from individuals. Now there are modes of surveying:
Questionnaire- its a form which consists of a set of questions which a correspondent asks from target audiences. This questionnaire either self administered by the respondent or administered by the researcher (enumerator) or trained investigator.
Points need to keep in mind while making questionnaire are:
The questionnaire should not be too long. The number of questions should be as minimum as possible.
The questionnaire should be easy to understand and avoid ambiguous or difficult words.
The questions should be arranged in an order such that the person answering should feel comfortable.
The series of questions should move from general to specific. The questionnaire should start from general questions and proceed to more specific ones.
The questions should be precise and clear. Example: Poor Ques What percentage of your income do you spend on clothing in order to look presentable? Good Ques What percentage of your income do you spend on clothing?
The questions should not be ambiguous or confusing. They should enable the respondents to answer quickly, correctly and clearly. Example: Poor Q Do you spend a lot of money on books in a month?
Good Q (Tick mark the appropriate option) How much do you spend on books in a month? (i) Less than Rs 200 (ii) Rs 200–300 (iii) Rs 300–400 (iv) More than Rs 400
The question should not use double negatives. Example: The questions starting with “Wouldn’t you” or “Don’t you” should be avoided, as they may lead to biased responses.
The question should not indicate alternatives to the answer. Example: Poor Q Would you like to do a job after college or be a housewife? Good Q What would you like to do after college ?
Now there are two types questions:
Closed-ended or structured questions- these questions are answered in ways first either- Yes or No or multiple choice questions.Closed-ended questions are easy to use, score and to codify for analysis.
Open-ended questions - these questions are open to many answers not bounded by yes or no and options. But these kinds of questions are difficult to interpret and hard to score. But can give you qualitative data. Example: Q. What is your view about globalisation?
Mode of Data Collection
There are three basic ways of collecting data:
(i) Personal Interviews- it is a method where interviewer and respondent talk face to face and get answers clearly and accurately. Interviewer can explain why this survey is being carried out and explain questions to respondents if they are unable to understand the questions. Misinterpretation and misunderstanding can be avoided. Watching the reactions of respondents can provide supplementary information
(ii) Mailing (questionnaire) Surveys- 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. It allows the researcher to have access to people in remote areas too and is less expensive.
(iii) Telephone Interviews- In a telephone interview, the investigator asks questions over the telephone. It can be conducted in a shorter time.
Comparison between Personal interviews, Mailing(questionnaire) Surveys and Telephone Interviews.
Pilot Survey
It's like the testing phase of a questionnaire before going for a full survey. A small group is being taken for this survey to test the questions and response to those questions.
benefit s of pilot survey:
To know the shortcomings and drawbacks of the questions.
Helps in assessing the suitability of questions
Helps in assessing the suitability of questions
Helps in clarity of instructions, performance of enumerators
Help the cost and time involved in the actual survey
CENSUS AND SAMPLE SURVEYS
Census- A survey, which includes every element of the population, is known as Census or the Method of Complete Enumeration. This survey was carried out from every house of the country, rural and urban areas of the country. It contains:
Demographic data on birth and death rates
Literacy
Employment
life expectancy
Size and composition of population
In India population is counted by census method, it is conducted by the Registrar General of India. The last Census of India was held in 2011. According to the Census 2011, the population of India was 121.09 crore, which was 102.87 crore in 2001. Census 1901 indicated that the population of the country was 23.83 crore.
Population and Sample
Population - In statistics population refers to target audiences where survey needs to be carried out. A population is always all the individuals/items who possess certain characteristics (or a set of characteristics), according to the purpose of the survey.This method would require huge expenditure, as a large number of enumerators have to be employed.
Sample- A sample refers to a group or section of the population from which information is to be obtained. When a researcher is unable to study the whole population due to large numbers then they choose a sample method to study.
A good sample (representative sample) is generally smaller than the population and is capable of providing reasonably accurate information about the population at a much lower cost and shorter time.
A sample can provide reasonably reliable and accurate information at a lower cost and shorter time.
More detailed information can be collected by conducting intensive enquiries
Need a smaller team of enumerators, it is easier to train them and supervise their work more effectively.
Example:
Research problem: To study the economic condition of agricultural labourers in Churachandpur district of Manipur.
Population: All agricultural labourers in Churachandpur district.
Sample: Ten per cent of the agricultural labourers in Churachandpur district.
Types of sampling :
Random Sampling- Where the individual units from the population (samples) are selected at random.In random sampling, every individual has an equal chance of being selected.
Example: The government wants to determine the impact of the rise in petrol price on the household budget of a particular locality. There are 300 houses(population) in the locality, now it's difficult, costly and time taking to study all 300 houses so it's decided to take a random sample of 30 houses,here every house gets an equal chance to get selected.
Non-Random Sampling - In this method individual units need to be selected by the surveyor. Example: lets again understand by above example- There are 300 houses(population) in the locality, now it's difficult, costly and time taking to study all 300 houses so it's decided to sample 30 houses but these houses are selected by researchers.
They are mainly selected on the basis of judgment, purpose, convenience or quota and are nonrandom samples.
SAMPLING AND NON-SAMPLING ERRORS
Sampling errors are the difference between the sampling result and actual population result or the difference between the actual value of a parameter of the population and its estimate (from the sample) is the sampling error. example:
Consider a case of the incomes of 5 farmers of Manipur.
The variable x (income of farmers) has measure-ments 500, 550, 600, 650, 700. We note that the population average of (500+550+600+650+700) ÷ 5 = 3000 ÷ 5 = 600.
Now, suppose we select a sample of two individuals where x has measurements of 500 and 600. The sample average is (500 + 600) ÷ 2 = 1100 ÷ 2 = 550. Here, the sampling error of the estimate = 600 (true value) – 550 (estimate) = 50
NON-SAMPLING ERRORS
Non- sampling errors occur due to those data or populations which remain unchecked or unsurveyed. Even by taking a large sample. Even a Census can contain non-sampling errors. Some of the non-sampling.
Some of the errors are:
Sampling Bias: it states choosing or not choosing sample members from the population. Example: a survey needs to be conducted to know which brand of a particular milk drink by people, now surveyors don't want to include low level income groups. Hence the result would vary a lot or might not be correct
Non-Response Errors - Non-response occurs if an interviewer is unable to contact a person listed in the sample or a person from the sample refuses to respond.
Errors in Data Acquisition-This type of error arises from recording of incorrect responses. Recording mistakes can also take place as the enumerators or the respondents may commit errors in recording or transcription the data, for example, he/ she may record 13 instead of 31.
CENSUS OF INDIA AND NSSO
There are some agencies related to data collection and calculation on state and national in India, like:
National level are Census of India, National Sample Survey (NSS)
Central Statistics Office (CSO)
Registrar General of India (RGI)
Directorate General of Commercial Intelligence and Statistics (DGCIS)
Labour Bureau
The Census of India provides the most complete and continuous demographic record of population. The Census has been regularly conducted every ten years since 1881.
The Census officials collect information on various aspects of population such as the size, density, sex ratio, literacy, migration, rural-urban distribution, they analyse and interpretate the data.
The NSS was established by the Government of India to conduct nationwide surveys on socio-economic issues
NSS provides periodic estimates of literacy, school enrolment, utilisation of educational services, employment, unemployment, manufacturing and service sector enterprises, morbidity, maternity, child care, utilisation of the public distribution system etc through its quarterly called journal Sarvekshana.
Data collected by NSS used by the government to form policies.Some of the surveys are:
The NSS 60th round survey (January–June 2004) was on morbidity and healthcare.
The NSS 68th round survey (2011-12) was on consumer expenditure.
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