Worksheet Solutions: Collection of Data - 2 | Economics Class 11 - Commerce PDF Download

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Q1: Primary data refers to information collected directly from _______________ for research purposes.
Ans: individuals or sources
Primary data is collected firsthand from individuals or sources specifically for the research being conducted.

Q2: Secondary data is data that has already been collected by _______________ for their own purposes.
Ans: others
Secondary data is pre-existing data collected by someone else for their own needs, which can be used for different research purposes.

Q3: A questionnaire is a research tool consisting of a series of _______________.
Ans: questions
A questionnaire is a set of questions designed to collect data from respondents.

Q4: An enumerator's role is to gather all the information and data required for a _______________.
Ans: survey
Enumerators collect data by conducting surveys and gathering information from respondents.

Q5: Open-ended questions do not limit respondents to predetermined _______________.
Ans: answer choices
Open-ended questions allow respondents to provide responses in their own words, without predefined answer options.

Q6: Sampling error can be reduced by increasing the _______________.
Ans: sample size
 Increasing the sample size in a survey can help reduce the sampling error, which is the difference between the sample estimate and the actual population characteristic.

Q7: Probability sampling allows for _______________ to be made about the population.
Ans: inferences
Probability sampling methods enable researchers to make statistically valid inferences about the entire population based on the sample data.

Q8: Non-sampling errors include data acquisition errors, non-response errors, and _______________.
Ans: measurement errors
Non-sampling errors encompass various errors that are not related to the sampling process, such as mistakes in data collection and measurement.

Q9: The National Sample Survey Office (NSSO) is a government agency in _______________.
Ans: India
The NSSO is a prominent government agency in India responsible for conducting various socioeconomic surveys.

Q10: NSSO was established in the year _______________.
Ans: 1950
The NSSO was established in 1950, shortly after India gained independence, to collect and publish statistical data on various aspects of the country.

Assertion and Reason Based

Q1: Assertion: Primary data is more cost-effective than secondary data.
Reason: Primary data is collected directly for the current research problem.
(a) Both assertion and reason are true, and the reason is the correct explanation of the assertion.
(b) Both assertion and reason are true, but the reason is not the correct explanation of the assertion.
(c) Assertion is true, but the reason is false.
(d) Assertion is false, but the reason is true.
Ans: (c)
 Primary data collection is often more expensive and time-consuming than using existing secondary data, so the assertion is true. However, the reason given is not accurate since primary data is collected for the specific research problem, making it more costly.

Q2: Assertion: Closed-ended questions are suitable for collecting qualitative data.
Reason: Respondents must choose a response from a predefined set of answer options.
(a) Both assertion and reason are true, and the reason is the correct explanation of the assertion.
(b) Both assertion and reason are true, but the reason is not the correct explanation of the assertion.
(c) Assertion is true, but the reason is false.
(d) Assertion is false, but the reason is true.
Ans: (c)
Closed-ended questions are typically used for collecting quantitative data, not qualitative data. The reason provided is incorrect.

Q3: Assertion: Sampling error can be reduced by increasing the sample size.
Reason: Sampling error is the difference between the sample estimate and the actual value of the population characteristic.
(a) Both assertion and reason are true, and the reason is the correct explanation of the assertion.
(b) Both assertion and reason are true, but the reason is not the correct explanation of the assertion.
(c) Assertion is true, but the reason is false.
(d) Assertion is false, but the reason is true.
Ans: (a)
Increasing the sample size can indeed reduce sampling error, and the reason correctly explains the assertion.

Q4: Assertion: Non-sampling errors are more difficult to minimize than sampling errors.
Reason: Non-sampling errors include data acquisition errors and sampling bias.
(a) Both assertion and reason are true, and the reason is the correct explanation of the assertion.
(b) Both assertion and reason are true, but the reason is not the correct explanation of the assertion.
(c) Assertion is true, but the reason is false.
(d) Assertion is false, but the reason is true.
Ans: (b)
The assertion is true as non-sampling errors can be challenging to minimize. However, the reason provided is not the correct explanation since non-sampling errors do not include sampling bias.

Q5: Assertion: The NSSO is a government agency that conducts regular socio-economic surveys in India.
Reason: The NSSO hires staff members from the Indian Statistical Service and the Subordinate Statistical Service.
(a) Both assertion and reason are true, and the reason is the correct explanation of the assertion.
(b) Both assertion and reason are true, but the reason is not the correct explanation of the assertion.
(c) Assertion is true, but the reason is false.
(d) Assertion is false, but the reason is true.
Ans: (a)
The NSSO conducts regular socio-economic surveys in India, and the reason correctly explains the assertion regarding the qualifications of its staff.

Very Short Answer Type Questions

Q1: Define primary data.
Ans: Primary data is data collected directly from original sources for a specific research purpose.

Q2: Give an example of secondary data source.
Ans: An example of a secondary data source is a published research paper or a government statistical report.

Q3: What is the advantage of using secondary data in research?
Ans: The advantage of using secondary data in research is that it is often cost-effective and saves time compared to collecting primary data.

Q4: Explain the role of an enumerator in statistical investigations.
Ans: An enumerator in statistical investigations is responsible for collecting data from respondents, often by conducting surveys or interviews.

Q5: What is the purpose of a pilot survey?
Ans: The purpose of a pilot survey is to test the data collection methods, questionnaire, and procedures before implementing a full-scale survey.

Q6: Define census method.
Ans: The census method involves collecting data from the entire population or universe rather than from a sample.

Q7: What is meant by the population or universe in statistics?
Ans: The population or universe in statistics refers to the entire group of elements or individuals about which data is of interest.

Q8: Define sampling errors.
Ans: Sampling errors are discrepancies between sample estimates and the actual population values caused by random variation in selecting samples.

Q9: What is non-sampling bias?
Ans: Non-sampling bias refers to errors in data collection, processing, or analysis that result from factors other than the sample selection process.

Q10: When was the NSSO set up?
Ans: The NSSO was set up in 1950 to conduct various socio-economic surveys in India.

Short Answer Type Questions

Q1: Differentiate between primary data and secondary data. 
Ans: Primary data is data collected directly for the specific research problem, while secondary data is pre-existing data collected for other purposes. Primary data is original and tailored to the research, while secondary data is readily available but may not fully match the research needs.

Q2: Explain the advantages and disadvantages of using a questionnaire as a data collection method. 
Ans: Advantages of using a questionnaire include its cost-effectiveness, ease of administration, and standardization. However, disadvantages include potential response bias, limited depth of information, and challenges in question design.

Q3: Describe the role of an enumerator in the data collection process. 
Ans: The enumerator's role involves collecting data directly from respondents, ensuring data accuracy, maintaining confidentiality, and often explaining the purpose of the survey. Enumerators play a crucial role in the data collection process.

Q4: Differentiate between open-ended and closed-ended questions in surveys. 
Ans: Open-ended questions allow respondents to provide unstructured, qualitative responses, while closed-ended questions offer predefined answer options, making them suitable for collecting quantitative data.

Q5: Discuss the advantages and disadvantages of conducting personal interviews as a data collection method. 
Ans: Advantages of personal interviews include the opportunity for clarifications, high response rates, and in-depth data. Disadvantages include time and cost, potential interviewer bias, and limited anonymity.

Q6: Explain the concept of probability sampling and provide an example. 
Ans: Probability sampling is a method in which each element in the population has a known, non-zero chance of being included in the sample. An example is simple random sampling, where each member has an equal chance of selection.

Q7: Define sampling bias and explain why it is important to minimize it in research.
Ans: Sampling bias is the systematic error introduced when a sample is not representative of the population. It's essential to minimize it to ensure the validity of research findings.

Q8: Describe the functions and significance of the National Sample Survey Office (NSSO) in India.
Ans: The NSSO in India conducts vital socio-economic surveys, providing data for policy formulation and program evaluation. Its staff includes members from the Indian Statistical Service and the Subordinate Statistical Service, ensuring high-quality data collection and analysis.

Long Answer Type Questions

Q1: Discuss the primary differences between primary data and secondary data, and provide examples of each. 
Ans: Primary data and secondary data are two fundamental types of data used in research, each with its unique characteristics and sources.

• Primary Data:
  • Primary data is collected directly for a specific research purpose. It is original and tailored to the research objectives.
  • Researchers gather primary data through methods like surveys, interviews, observations, or experiments.
  • Examples of primary data include survey responses from a questionnaire designed for a particular study, interview transcripts, experimental measurements, or observations recorded during fieldwork.
• Secondary Data:
  • Secondary data is data that has already been collected by others for their own purposes, and it may not have been initially intended for the current research.
  • Researchers obtain secondary data from sources like government reports, academic publications, company records, or historical archives.
  • Examples of secondary data include census data, previously published research findings, financial reports, or historical weather records.

Q2: Explain the various types of non-probability sampling methods, and discuss their advantages and disadvantages. 
Ans: Non-probability sampling methods are techniques in which not every member of the population has a known chance of being included in the sample. These methods are used in situations where it's challenging to create a random or representative sample.

• Convenience Sampling:
  • Advantages: Quick and cost-effective, especially for pilot studies or exploratory research.
  • Disadvantages: Highly susceptible to bias, as it relies on readily available subjects, often leading to non-representative samples.
• Judgmental or Purposive Sampling:
  • Advantages: Useful for studies where specific expertise is required or when studying a rare population.
  • Disadvantages: Prone to researcher bias, as individuals are selected based on their judgment.
• Snowball Sampling:
  • Advantages: Effective for hard-to-reach or hidden populations, such as drug users or marginalized groups.
  • Disadvantages: Initial seeds may introduce bias, and sample size can be challenging to control.
• Quota Sampling:
  • Advantages: Allows for stratification by key characteristics, ensuring proportional representation.
  • Disadvantages: Prone to non-response bias if subjects refuse participation.

Non-probability sampling methods are subject to various biases and may not provide a representative sample. Researchers should be aware of these limitations when choosing such methods.

Q3: Describe the concept of sampling error, its causes, and ways to minimize it in research. 
Ans: Sampling error is the difference between the results obtained from a sample and the actual values that would have been obtained if the entire population were surveyed. It is inherent in all sampling methods and arises from several sources:

• Random Chance: Even with random sampling, there is variability due to chance. Not every sample will perfectly represent the population.
• Sampling Frame Issues: Errors can occur if the sampling frame (the list from which the sample is drawn) is incomplete, outdated, or inaccurate.
• Non-response: When a portion of the selected sample does not respond, it can introduce bias and increase sampling error.

Minimizing sampling error involves several strategies:

• Increasing Sample Size: A larger sample size generally reduces sampling error, as it provides a more accurate estimate of the population parameters.
• Random Sampling: Employing true random sampling methods helps mitigate bias, as each member of the population has an equal chance of selection.
• Stratified Sampling: Dividing the population into strata and sampling proportionally within each stratum can improve representativeness.
• Systematic Sampling: Selecting every nth member from the sampling frame can reduce the risk of clustering.

Q4: Elaborate on the factors that can lead to non-sampling errors in data collection, and provide strategies to reduce their impact.
Ans: Non-sampling errors are deviations from the true population values that are not related to the sampling process. They can be equally or even more detrimental than sampling errors. Some factors contributing to non-sampling errors include:

• Data Collection Errors: Mistakes made during data entry, data recording, or data transmission. This may include typographical errors, data coding errors, or data misinterpretation.
• Non-response Bias: Occurs when selected individuals or units in the sample do not participate, leading to a biased sample. To reduce non-response bias, follow-up with non-respondents and ensure a high response rate.
• Coverage Errors: Arise when the sampling frame does not fully represent the population. To address this, update and maintain accurate sampling frames.
• Response Errors: Happen when respondents provide inaccurate or incomplete information. Training interviewers, using clear and well-structured questionnaires, and ensuring respondent confidentiality can minimize response errors.
• Instrument Errors: Result from problems with data collection instruments, such as poorly designed surveys or faulty measurement devices. Careful instrument design and testing can reduce instrument errors.

To reduce the impact of non-sampling errors, it's crucial to implement rigorous data collection procedures, ensure data quality control, and apply consistent and standardized methods throughout the research process. Verification and validation processes can help identify and correct errors in the data. Additionally, continuous training and monitoring of data collection staff can minimize errors due to human factors.