Class 11 Statistics Notes Chapter 2 (Collection of data) – Statistics For Economics Book

Detailed Notes with MCQs of Chapter 2: Collection of Data from your Statistics for Economics textbook. This chapter is fundamental, not just for your Class 11 exams, but also forms the bedrock for understanding statistical analysis often tested in various government exams. Pay close attention.

Chapter 2: Collection of Data - Detailed Notes

1. Introduction: What is Data and Why Collect It?

• Data: Facts, figures, or information collected for a specific purpose. In economics, data helps understand economic problems, formulate policies, and evaluate their effectiveness.
• Statistical Enquiry/Investigation: A systematic process of collecting statistical data related to a specific problem or field of study.
• Need for Data: Data provides evidence, helps in planning (e.g., government budgets, business expansion), forecasting (e.g., predicting demand, inflation), and comparing economic phenomena (e.g., comparing GDP growth rates across countries).

2. Sources of Data

Data can be obtained from two primary types of sources:

• A. Primary Data:

  • Definition: Data collected for the first time by the investigator or agency directly from the source (the field of enquiry). It's original data.
  • Characteristics: First-hand information, collected specifically for the current study, requires more time, money, and effort.
  • Methods of Collecting Primary Data:
    • i) Direct Personal Investigation:
      • Investigator directly contacts the informants/respondents and collects information face-to-face.
      • Merits: High degree of originality and accuracy, reliable, allows for clarification of doubts, supplementary information can be gathered.
      • Demerits: Expensive, time-consuming, possibility of personal bias (investigator's influence), limited coverage (difficult for large areas).
      • Suitability: Intensive study, confidential information needed, area of investigation is limited.
    • ii) Indirect Oral Investigation:
      • Information is collected indirectly from third parties or witnesses who are expected to possess the necessary information about the problem under investigation (used when informants are reluctant or unavailable).
      • Merits: Wider coverage possible, less expensive and time-consuming than direct investigation, opinions of experts can be sought.
      • Demerits: Information is second-hand (less accurate), possibility of bias from the witness, witness might be careless or indifferent.
      • Suitability: When direct contact is not possible, informants are hesitant, area is large.
    • iii) Information from Local Sources or Correspondents:
      • Investigator appoints local agents or correspondents in different areas to collect and transmit information. Used by newspapers, magazines, government departments (e.g., for crop estimates).
      • Merits: Economical, wide coverage, suitable for regular and continuous information.
      • Demerits: Low degree of accuracy (due to potential bias or carelessness of correspondents), lack of uniformity in collection methods, delay in collection.
      • Suitability: Regular information needed from a wide area, high accuracy not paramount.
    • iv) Mailed Questionnaire Method:
      • A questionnaire (list of questions) is prepared and mailed to informants with a request to fill it out and return it by a specific date. A cover letter explaining the purpose is usually included.
      • Merits: Most economical (saves time, money, labour), wide coverage (can reach remote areas), free from investigator bias, informants can answer at their convenience.
      • Demerits: Low response rate (informants may not return it), possibility of misunderstanding questions, cannot be used for illiterate informants, lack of flexibility (questions cannot be changed).
      • Suitability: When the area is vast, informants are literate.
    • v) Schedules filled by Enumerators:
      • A schedule (similar to a questionnaire, but usually more detailed) is prepared. Enumerators (trained field workers) personally visit informants, ask questions, and fill the schedule themselves.
      • Merits: Wide coverage, suitable for literate and illiterate informants, higher accuracy and response rate (due to personal contact), doubts can be clarified, less chance of misinterpretation.
      • Demerits: Most expensive method, time-consuming, requires training of enumerators, possibility of enumerator bias.
      • Suitability: Large-scale surveys (like Census), when informants are diverse (including illiterate), high accuracy is required.

• B. Secondary Data:

  • Definition: Data that has already been collected by someone else for some other purpose and is available in published or unpublished form. It's second-hand data.
  • Characteristics: Already processed (at least partially), readily available, requires less time and money compared to primary data collection.
  • Sources of Secondary Data:
    • i) Published Sources:
      • Government Publications: Central and State Governments (e.g., Statistical Abstract of India by NSO, Economic Survey, Census reports by RGI, RBI Bulletins, Agricultural Statistics by Ministry of Agriculture).
      • Semi-Government Publications: Municipalities, District Boards.
      • Reports of Committees and Commissions: Appointed by the government (e.g., Finance Commission reports).
      • Private Publications: Trade associations, research institutions (e.g., NCAER), journals and newspapers (e.g., Economic Times), market reviews.
      • International Publications: IMF, World Bank, WHO, ILO publications.
    • ii) Unpublished Sources:
      • Data collected by government organizations, private offices, research scholars, etc., but not published. Available in files, records, registers.
  • Precautions Before Using Secondary Data: Before using secondary data, its reliability, suitability, and adequacy must be checked. Consider:
    • Ability of the Collecting Organisation: Was the original agency competent and unbiased?
    • Objective and Scope: Was the objective of the original collection relevant to your current purpose? Was the scope appropriate?
    • Method of Collection: Was the original data collected using appropriate methods? (e.g., Was the sample representative?)
    • Time and Conditions of Collection: Is the data outdated? Were the conditions during collection relevant to the current context?
    • Definition of Units: Were the units of measurement (e.g., income, weight) defined similarly?
    • Accuracy: What was the level of accuracy maintained in the original collection?

3. Key Concepts in Data Collection

• Investigator: The person who plans and conducts the statistical enquiry.
• Enumerator: The person who actually collects the data (often works under the investigator, especially in large surveys).
• Respondent/Informant: The person from whom the statistical information is collected.
• Population or Universe: The complete set of all possible items/individuals related to a particular study (e.g., all farmers in a state, all students in a school).
• Sample: A subset or a representative part of the population selected for study. Studying a sample is often more practical than studying the entire population.
• Pilot Survey (Pre-testing): A try-out survey conducted on a small scale before the main survey. It helps to:
  • Test the suitability of the questionnaire/schedule.
  • Assess the clarity of questions and instructions.
  • Estimate the time and cost involved in the main survey.
  • Train the enumerators.

4. Questionnaire and Schedule

• Questionnaire: A list of questions pertaining to the enquiry, usually sent by mail or distributed to respondents who fill it themselves.
• Schedule: A list of questions pertaining to the enquiry, which is carried and filled by the enumerator after asking the questions to the respondent.
• Difference: The key difference lies in who fills the form. Questionnaire = Respondent; Schedule = Enumerator.
• Qualities of a Good Questionnaire/Schedule:
  • Limited Number of Questions: Keep it as short as possible.
  • Simplicity: Use clear, unambiguous language. Avoid jargon.
  • Logical Sequence: Questions should follow a logical order.
  • No Leading Questions: Avoid questions that suggest an answer (e.g., "Don't you think...?").
  • Avoid Controversial/Personal Questions: Unless absolutely necessary and handled sensitively.
  • Instructions: Clear instructions for filling should be provided.
  • Pre-testing: Conduct a pilot survey to test it.
  • Cross-Verification: Include questions that can cross-check information.
  • Request for Return: (For questionnaires) Politely request timely return.

5. Census vs. Sample Survey

• A. Census Method:
  • Definition: Data is collected from every single item/unit of the population or universe. (e.g., Population Census of India).
  • Suitability: When the population size is small, detailed information about every unit is required, high accuracy is essential, units are heterogeneous.
  • Merits: Highly accurate and reliable, provides extensive and detailed information.
  • Demerits: Very expensive, time-consuming, requires a large number of enumerators, may not be feasible if the population is infinite or testing is destructive.
• B. Sample Method:
  • Definition: Data is collected from only a representative part (sample) of the population. Conclusions about the population are drawn based on the sample results.
  • Suitability: When the population size is very large or infinite, high accuracy is not paramount, quick results are needed, resources (time, money) are limited, units are broadly homogeneous, census is impractical (e.g., destructive testing like checking bulb life).
  • Merits: Economical (less cost), time-saving, quicker results, allows for more detailed study of selected units, administrative convenience, more scientific (allows estimation of error).
  • Demerits: Less accurate than census (especially if the sample is not representative), possibility of bias in sample selection, difficulty in selecting a truly representative sample, requires specialized knowledge for sampling techniques.

6. Sampling Methods (Brief Overview)

• Random Sampling: Every item in the population has an equal chance of being selected. (e.g., Lottery method, Random number tables). More scientific, less biased.
  • Simple Random Sampling: Each unit has an equal probability of selection.
  • Stratified Sampling: Population divided into strata (groups), then random samples drawn from each stratum.
• Non-Random Sampling: Items are selected based on judgement, convenience, or quota, not chance. Prone to bias.
  • Convenience Sampling: Selecting easily accessible units.
  • Judgement Sampling: Investigator uses their judgement to select 'representative' units.
  • Quota Sampling: Pre-set quotas for different groups are filled using non-random methods.

7. Errors in Data Collection

• Sampling Errors: The difference between the sample result and the true population result. Arises because only a part of the population is studied. Can be reduced by increasing sample size and using appropriate sampling methods. Occurs only in sample surveys.
• Non-Sampling Errors: Errors that can occur in both census and sample surveys. More serious as they are harder to estimate. Examples include:
  • Errors in Data Acquisition: Incorrect responses, recording errors by enumerators.
  • Non-Response Errors: Failure to collect data from some units in the sample/census.
  • Measurement Errors: Faulty questionnaires, poor training of enumerators, respondent bias.

8. Major Agencies for Data Collection in India

• National Statistical Office (NSO): Formed by merging NSSO (National Sample Survey Office) and CSO (Central Statistics Office). It's the apex statistical body. Conducts large-scale sample surveys (like employment, consumption expenditure), compiles National Accounts Statistics (GDP, etc.), Index of Industrial Production (IIP).
• Registrar General of India (RGI): Conducts the decennial Population Census. Collects demographic data.
• Reserve Bank of India (RBI): Collects and publishes data related to banking, finance, and monetary indicators.
• Labour Bureau: Collects data on labour statistics (wages, employment in organised sector, industrial disputes).
• Directorate General of Commercial Intelligence and Statistics (DGCI&S): Collects and compiles foreign trade statistics.

Multiple Choice Questions (MCQs)

1. Data collected by the investigator for the first time from the source is called:
   a) Secondary Data
   b) Primary Data
   c) Internal Data
   d) External Data

2. Which method of primary data collection is most suitable when the area of investigation is very large and informants are literate?
   a) Direct Personal Investigation
   b) Indirect Oral Investigation
   c) Mailed Questionnaire
   d) Schedules filled by Enumerators

3. Information gathered from published government reports like the Economic Survey is an example of:
   a) Primary Data
   b) Secondary Data
   c) Sample Data
   d) Census Data

4. A pre-test conducted before the main survey to check the questionnaire and estimate time/cost is known as:
   a) Census Survey
   b) Sample Survey
   c) Pilot Survey
   d) Random Survey

5. In which method does the enumerator personally visit the informants with a list of questions?
   a) Mailed Questionnaire
   b) Indirect Oral Investigation
   c) Schedules filled by Enumerators
   d) Information from Correspondents

6. Which of the following is a merit of the Census method?
   a) It is less expensive.
   b) It requires less time.
   c) It provides detailed information about every unit.
   d) It is suitable for destructive testing.

7. The difference between the result obtained from a sample and the true population value is called:
   a) Non-Sampling Error
   b) Measurement Error
   c) Sampling Error
   d) Bias Error

8. Which agency is primarily responsible for conducting the Population Census in India?
   a) National Statistical Office (NSO)
   b) Reserve Bank of India (RBI)
   c) Registrar General of India (RGI)
   d) Labour Bureau

9. Which of the following is a precaution needed before using secondary data?
   a) Check the ability of the collecting agency
   b) Check the objective and scope of the original study
   c) Check the time period of data collection
   d) All of the above

10. When every item of the universe is selected for data collection, the method is called:
    a) Sample Method
    b) Quota Method
    c) Census Method
    d) Stratified Method

Answer Key for MCQs:

1. b
2. c
3. b
4. c
5. c
6. c
7. c
8. c
9. d
10. c

Make sure you understand these concepts thoroughly. Data collection is the first crucial step in any statistical analysis, and getting it right is essential. Revise these notes and try to relate them to real-world examples you see in newspapers or government reports. Good luck with your preparation!