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झारखण्ड बोर्ड (JAC) • कक्षा XI • Economics • अध्याय 2
अनुमानित समय: 45 Mins
प्रगति: अध्ययनरत

आंकड़ों का संग्रह (Collection of Data)

In CBSE Class 11 Economics, "Collection of Data" provides an authoritative, methodological master guide on the foundational first step of empirical economic inquiry. This comprehensive chapter deconstructs Primary Data vs Secondary Data, primary data collection methods (Direct Personal Investigation, Indirect Oral Investigation, Information from Local Correspondents, Mailed Questionnaires, and Schedules with Enumerators), principles of designing an ideal Questionnaire, pilot surveys (pre-testing), Census Method (Complete Enumeration) vs Sample Method, methods of sampling (Random Sampling [Simple Random vs Stratified Random Sampling] vs Non-Random Sampling [Purposive, Quota, Convenience]), statistical errors (Sampling Errors [biased vs unbiased] vs Non-Sampling Errors [data acquisition, non-response, measurement]), and national secondary data institutions (Census of India, National Sample Survey Organisation [NSSO / NSO]) aligned with the 2026–27 CBSE curriculum.

अध्याय CBT ऑनलाइन टेस्ट दें सभी अध्याय देखें
प्रस्तावना अध्याय अवधारणाएँ आर्थिक सूत्र एवं सिद्धांत अध्याय सारांश स्व-मूल्यांकन अभ्यास टेस्ट दें

How Did the Literary Digest Poll with 2.4 Million Ballots Get Humiliated by a Statistician with Only 50,000?

In the 1936 United States Presidential Election, the prestigious magazine Literary Digest conducted the largest political poll in human history, mailing out over 10 million straw ballots and receiving an unprecedented 2.4 million completed responses. The magazine confidently predicted that Alfred Landon would defeat Franklin D. Roosevelt in a colossal landslide (57% to 43%). Meanwhile, a young statistician named George Gallup surveyed a tiny sample of just 50,000 voters and predicted Roosevelt would win comfortably. When the election results were certified, Roosevelt won in one of the greatest landslides in American history with 60.8% of the popular vote! The Literary Digest was financially ruined and folded shortly after. How did a sample of 2.4 million fail so catastrophically while a sample of 50,000 succeeded brilliantly? The answer lies in Sampling Bias: the magazine selected names from telephone directories and luxury automobile registrations during the Great Depression—surveying only the wealthy, while ignoring the millions of unemployed working-class voters who supported Roosevelt! Let's master the science of collecting unbiased economic data.

यह अध्याय क्यों महत्वपूर्ण है

Every economic policy is only as reliable as the raw data upon which it is built ("garbage in, garbage out"). If an inflation survey queries the wrong sample or an enumerator writes ambiguous questions, national monetary policy will fail. Understanding how the Census of India operates, how the NSSO surveys rural poverty, and how to eliminate non-sampling errors is vital for every economist and researcher.

अध्ययन से पूर्व (आवश्यक ज्ञान)

  • Introduction to statistics concepts from Chapter 9.
  • Basic understanding of surveys, forms, and questionnaires.
  • Elementary probability and percentage calculations.

इस अध्याय के लक्ष्य

  • Distinguish between Primary Data (first-hand collection) and Secondary Data (existing records).
  • Evaluate the 5 methods of collecting Primary Data: Direct Personal, Indirect Oral, Correspondents, Mailed Questionnaires, and Enumerators.
  • Formulate an ideal Questionnaire following scientific design principles (brief, unambiguous, cross-checks, logical order).
  • Explain the role and importance of a Pilot Survey (pre-testing questionnaires).
  • Compare the Census Method (Complete Enumeration) with the Sample Method (Representative subset).
  • Differentiate between Random Sampling (Lottery, Random Numbers, Stratified) and Non-Random Sampling (Purposive, Quota).
  • Analyze Sampling Errors vs Non-Sampling Errors (Non-response, measurement, tabulating errors).
  • Identify India's premier statistical agencies: Census of India (Registrar General) and NSSO/NSO.

अध्याय रूपरेखा एवं प्रगति

1 1. Primary Data vs Secondary Data
2 2. Methods of Collecting Primary Da...
3 3. Census Method vs Sample Method
4 4. Statistical Errors & National Da...

सम्पूर्ण सैद्धांतिक एवं वैचारिक अध्ययन

1. Primary Data vs Secondary Data

Understand

Statistical data is categorized based on its original source of origin:

BasisPrimary DataSecondary Data
OriginalityOriginal in character; collected from the original source for the first time by the investigator.Not original; compiled from existing records published or unpublished by another agency.
Cost & TimeHighly expensive, labor-intensive, and requires considerable time to conduct field surveys.Economical and quickly accessible from libraries, websites, and government bulletins.
SuitabilityTailored precisely to the specific objective of the inquiry; requires zero adjustment.Collected for another purpose; requires thorough scrutiny for reliability, adequacy, and bias.

2. Methods of Collecting Primary Data & Questionnaire Design

Primary Collection Methods
  1. 1. Direct Personal Investigation: The investigator personally interviews informants on the spot. Produces highly accurate, original, and uniform data, but is unfeasible for vast geographic areas and is prone to investigator bias.
  2. 2. Indirect Oral Investigation: The investigator interviews third-party witnesses who possess reliable information about the subject (used in police investigations or labor disputes).
  3. 3. Information from Local Correspondents: Local agents appointed in different areas collect and submit periodic reports (used by news media and crop estimation agencies).
  4. 4. Mailed Questionnaire Method: Questionnaires are sent via mail/email with a request to fill and return. Covers vast geographic areas cheaply, but suffers from low response rates and cannot be used among illiterate populations.
  5. 5. Schedules Sent Through Enumerators: Trained enumerators carry schedules, ask questions, and record answers directly. Highly accurate, covers illiterate informants, but is the most expensive method.
Qualities of a Good Questionnaire & Pilot Surveys:
  • Keep the number of questions to an absolute minimum (concise).
  • Questions must be clear, simple, and unambiguous; avoid complex mathematical calculations.
  • Avoid leading questions ("Don't you agree our school is the best?") and offensive personal inquiries.
  • Follow a logical sequence from general introductory to specific topics.
  • Pilot Survey (Pre-Testing): A preliminary trial survey conducted on a small sample before launching the full-scale survey. Identifies confusing questions, estimates survey time/costs, and tests enumerator preparedness.

3. Census Method vs Sample Method

Census vs Sample
A. Census Method (Complete Enumeration):

A statistical inquiry where information is collected from every single unit or element in the entire population or universe (e.g., the decennial Census of India). Guarantees high accuracy and comprehensive coverage, but requires massive financial expenditure and enormous manpower.

B. Sample Method (Representative Inquiry):

A statistical inquiry where information is collected from only a representative subset (sample) selected from the population, and conclusions are generalized to the entire universe.

Methods of Sampling:
  • 1. Random Sampling: Every unit in the universe has a known, equal, non-zero probability of being selected (unbiased):
    • Simple Random Sampling: Using the lottery method or random number tables (Tippett's tables).
    • Stratified Random Sampling: When the universe is heterogeneous, it is divided into homogeneous strata (e.g., income tiers), and random samples are drawn proportionally from each stratum.
  • 2. Non-Random Sampling: Selection depends on investigator discretion or quotas:
    • Purposive / Deliberate Sampling: Investigator chooses units deliberately deemed representative.
    • Quota Sampling: Interviewers are assigned specific quotas of respondents based on demographic categories.
    • Convenience Sampling: Units chosen simply based on physical ease of access.

4. Statistical Errors & National Data Institutions in India

Errors & Indian Statistical Bodies
A. Sampling Errors vs Non-Sampling Errors:
  • Sampling Errors: Errors arising solely due to the fact that only a fraction of the population (a sample) is studied rather than the whole census. As sample size ($n$) increases, sampling errors decrease! $$\text{Sampling Error} = \text{Sample Statistic} - \text{True Population Parameter}$$
  • Non-Sampling Errors: Human and procedural mistakes present in BOTH sample surveys and complete censuses:
    • Errors of Non-Response: Informants refuse to answer or cannot be contacted.
    • Errors of Measurement: Faulty measuring instruments, ambiguous questions, or untruthful answers.
    • Data Processing Errors: Mistakes during manual coding, editing, and data tabulation.
B. Premier National Statistical Agencies in India:
  • Census of India: Conducted every 10 years by the Office of the Registrar General and Census Commissioner of India (Ministry of Home Affairs). Provides comprehensive demographic, literacy, and housing data.
  • National Sample Survey Organisation (NSSO / NSO): Operates under the Ministry of Statistics and Programme Implementation (MoSPI). Conducts nationwide continuous socio-economic sample surveys on consumer expenditure, employment-unemployment, and agricultural conditions.

प्रमुख आर्थिक सूत्र, व्यावसायिक सिद्धांत एवं मानक

Sampling Error Formula
$$\text{Sampling Error} = |\bar{x} - \mu|$$
Absolute difference between sample mean and true population mean.
Sample Size vs Sampling Error
$$\text{Sampling Error} \propto \frac{1}{\sqrt{n}}$$
Sampling error decreases inversely with the square root of sample size.

Data Collection Methods Architecture

Collection of Data: Methodological Framework 1. PRIMARY DATA METHODS • Direct Personal Investigation (High accuracy) • Indirect Oral (Third-party witness interviews) • Local Correspondents (Journalism/crops) • Mailed Questionnaire • Enumerator Schedules 2. CENSUS VS SAMPLE METHOD • Census: 100% complete enumeration (Census of India) • Sample: Representative subset of universe • Random: Lottery, Tippett tables, Stratified • Non-Random: Purposive, Quota, Convenience 3. QUESTIONNAIRE & PILOT SURVEY • Short, clear, unambiguous, no leading bias • Logical ordering • Cross-checking questions • Pilot Survey: Pre-testing on small sample • Detects flaws, trains staff, estimates costs 4. ERRORS & INDIAN AGENCIES • Sampling Errors: Due to sample size (falls with $n$) • Non-Sampling Errors: Non-response, measurement • Census of India: Decennial population survey • NSSO / NSO: Continuous socio-economic surveys

अध्याय का सार संक्षेप एवं 10 मुख्य निष्कर्ष

मुख्य बिंदु 1
Primary data is original data collected first-hand; Secondary data is gathered from existing published or unpublished records.
मुख्य बिंदु 2
Primary data collection methods include Direct Personal Investigation, Indirect Oral, Local Correspondents, Mailed Questionnaires, and Enumerators.
मुख्य बिंदु 3
A good questionnaire has a limited number of clear, non-offensive, and non-leading questions arranged in logical order.
मुख्य बिंदु 4
A pilot survey is a small-scale trial run conducted to pre-test a questionnaire and detect flaws before the full survey.
मुख्य बिंदु 5
The Census method studies 100% of units in the population; the Sample method studies a representative subset.
मुख्य बिंदु 6
In Random Sampling, every unit in the universe has a known, equal probability of selection, eliminating personal bias.
मुख्य बिंदु 7
Stratified random sampling is used when the population is heterogeneous by dividing it into homogeneous strata.
मुख्य बिंदु 8
Sampling error is the difference between sample statistics and population parameters, decreasing as sample size increases.
मुख्य बिंदु 9
Non-sampling errors (non-response, measurement, processing) occur in both sample surveys and complete censuses.
मुख्य बिंदु 10
The Census of India provides decennial demographic data, while the NSSO/NSO conducts nationwide socio-economic surveys.

स्व-मूल्यांकन अभ्यास (Check Your Understanding)

मूल वैचारिक स्पष्टता की जांच के लिए नैदानिक प्रश्न। पहले स्वयं हल करें, फिर उत्तर देखें।

1
Differentiate between "Primary Data" and "Secondary Data" on the basis of: (a) Originality, (b) Cost and Time, (c) Need for adjustment.
उत्तर एवं व्याख्या देखें
उत्तर:

• (a) Originality: Primary data is completely original in character as it is collected first-hand from source; Secondary data is not original, having already been collected and processed by an external agency.
• (b) Cost and Time: Primary data requires substantial financial expenditure, large field teams, and extensive time; Secondary data is economical and quickly accessible from publications or digital repositories.
• (c) Need for Adjustment: Primary data is collected specifically for the study's objective and requires no adjustment; Secondary data was collected for another purpose and must be rigorously scrutinized for reliability, adequacy, and bias.


Primary is original, expensive, and fits objective; Secondary is existing, cheap, and requires careful scrutiny.
2
What is a "Pilot Survey" (Pre-testing)? State three major advantages of conducting a pilot survey.
उत्तर एवं व्याख्या देखें
उत्तर:

A Pilot Survey is a preliminary trial run of the questionnaire conducted on a small, representative sample of respondents prior to launching the large-scale statistical investigation.
Advantages:
1. Identifies Ambiguous Questions: Detects confusing, poorly phrased, or culturally offensive questions so they can be revised.
2. Estimates Time and Financial Costs: Provides a realistic assessment of the total budget and duration required for field operations.
3. Evaluates Enumerator Preparedness: Assesses how well enumerators administer the questionnaire and handle respondent hesitations.


Small trial run to pre-test questionnaire, identify confusing questions, and estimate survey time/costs.
3
Compare the "Census Method" with the "Sample Method" of data collection. State one situation where the Census method is mandatory.
उत्तर एवं व्याख्या देखें
उत्तर:

• Census Method: Examines every single individual unit in the entire statistical population (complete enumeration). Yields exhaustive detail, but requires massive financial resources and time.
• Sample Method: Examines only a representative fraction (sample) selected from the population, generalizing findings to the whole universe. It is faster, cheaper, and often more accurate.
• Mandatory Situation: When destructive testing is NOT involved and absolute accuracy across every single unit is legally required—such as the decennial national population census or critical aerospace safety inspections.


Census covers 100% of units; Sample covers a subset. Census is mandatory for national population counts.
4
What is "Stratified Random Sampling"? When is it preferred over Simple Random Sampling?
उत्तर एवं व्याख्या देखें
उत्तर:

Stratified Random Sampling is a method where a heterogeneous population is divided into distinct, non-overlapping homogeneous sub-groups called strata (based on traits like income, age, gender, or geographic region). A random sample is then drawn proportionally or disproportionately from each stratum.
Preference: It is strongly preferred when the population is heterogeneous (diverse). Simple random sampling might accidentally omit important minority sub-groups, whereas stratified sampling guarantees proportional representation of every sub-segment.


Dividing heterogeneous population into homogeneous strata; preferred when population is highly diverse.
5
Distinguish between "Sampling Errors" and "Non-Sampling Errors". Which of these errors decreases as sample size increases?
उत्तर एवं व्याख्या देखें
उत्तर:

• Sampling Errors: Errors that occur purely because only a sample of the population is surveyed instead of the entire universe. As the sample size ($n$) increases, sampling errors systematically decrease because the sample approaches the full population.
• Non-Sampling Errors: Errors that arise from human mistakes, such as respondent non-response, measurement inaccuracies, misleading questionnaires, or manual data entry errors. Non-sampling errors can occur in BOTH sample surveys and 100% complete censuses, and often expand as the scale of the survey grows!


Sampling errors arise from observing a subset and decrease with larger sample size; Non-sampling errors arise from human mistakes.
6
State four essential guidelines for constructing an effective Questionnaire.
उत्तर एवं व्याख्या देखें
उत्तर:
  1. Keep it Brief: Restrict the total number of questions to what is strictly necessary.
    2. Clear and Unambiguous Phrasing: Use simple, everyday vocabulary; avoid technical jargon or double negatives.
    3. Avoid Leading Questions: Do not phrase questions in a way that suggests a desired answer (e.g., avoid "Don't you think taxes are too high?").
    4. Logical Progression: Arrange questions sequentially from general, simple queries to more specific inquiries, avoiding sensitive personal questions early on.

Brief, unambiguous phrasing, avoiding leading bias, and structured in logical sequence.
7
What is the full form of NSSO? Under which Union Ministry does it function, and what is its primary responsibility?
उत्तर एवं व्याख्या देखें
उत्तर:

• Full Form: National Sample Survey Organisation (now integrated into the National Statistical Office, NSO).
• Ministry: Functions under the Ministry of Statistics and Programme Implementation (MoSPI), Government of India.
• Primary Responsibility: To design, execute, and publish nationwide, continuous, large-scale socio-economic sample surveys on household consumer expenditure, employment, poverty, and industrial output.


National Sample Survey Organisation under MoSPI; conducts nationwide socio-economic sample surveys.
8
Why is the "Mailed Questionnaire Method" unsuitable for rural surveys in developing countries?
उत्तर एवं व्याख्या देखें
उत्तर:
  1. High Illiteracy Rates: Illiterate rural respondents cannot read the questions or write responses without assistance.
    2. Low Response Rates: Respondents often discard mailed questionnaires, resulting in significant non-response bias and incomplete datasets.

High rural illiteracy prevents independent completion, leading to high non-response rates.
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कक्षा 11 Economics के सभी अध्याय

अध्याय 1: परिचय (Introduction) (Introduction) अध्याय 2: आंकड़ों का संग्रह (Collection of Data) अध्याय 3: आंकड़ों का संगठन (Organisation of Data) अध्याय 4: डेटा की प्रस्तुति (Presentation of Data) अध्याय 5: केन्द्रीय प्रवृत्ति के उपाय (Measures of Central Tendency) अध्याय 6: विक्षेपण के माप (Measures of Dispersion) अध्याय 7: सहसंबंध (Correlation) (Correlation) अध्याय 8: सूचकांक संख्या (Index Numbers) अध्याय 9: स्वतंत्रता की पूर्व संध्या पर भारतीय अर्थव्यवस्था (Indian Economy on the Eve of Independence) अध्याय 10: भारतीय अर्थव्यवस्था (1950-1990) (Indian Economy 1950-1990) अध्याय 11: उदारीकरण, निजीकरण और वैश्वीकरण: एक समीक्षा (Liberalisation, Privatisation and Globalisation: An Appraisal) अध्याय 12: गरीबी (Poverty) अध्याय 13: भारत में मानव पूँजी का निर्माण (Human Capital Formation in India) अध्याय 14: ग्रामीण विकास (Rural Development) (Rural Development) अध्याय 15: रोजगार: संवृद्धि, अनौपचारीकरण एवं अन्य मुद्दे (Employment: Growth, Informalisation and Other Issues) अध्याय 16: आधारभूत संरचना (Infrastructure) अध्याय 17: पर्यावरण एवं सतत विकास (Environment & Sustainable Development) अध्याय 18: भारत और इसके पड़ोसी देशों के तुलनात्मक विकास अनुभव (Comparative Development Experiences of India and Its Neighbours)

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