Collection of Data Class 11 Notes: CBSE (Statistics For Economics) Chapter 2

Introduction to Data Collection

Data: Refers to factual information, figures, or statistics that serve as the foundation for analysis and decision-making.

Importance of Data:

1. Helps in understanding economic conditions.

2. Facilitates decision-making and problem-solving in research.

Types of Data:

Primary Data: Data collected by the investigator directly for the first time. It is original and specific to the study.

Example: Survey responses collected through questionnaires.

Secondary Data: Data that already exists, collected by someone else for a different purpose but used in the current research.

Example: National census reports.

Primary Data

Information was collected directly from the source by the researcher for the first time.

Characteristics:

1. Highly reliable as it is specific to the research objective.

2. Often time-consuming and expensive to collect.

Methods of Collecting Primary Data:

1. Direct Personal Investigation:

• The investigator personally interacts with respondents and gathers data.

• Suitable for small-scale studies.

• Example: Interviewing farmers about their crop yield.

2. Indirect Oral Investigation:

• Information is collected from third parties who know the subject.

• Example: Gathering information about an accident from witnesses.

3. Schedules and Questionnaires:

• Schedule: The investigator fills the data collection form based on respondents' answers.

• Questionnaire: A set of written questions provided to respondents for them to fill.

4. Local Reports:

• Information is collected through local sources, such as community leaders or officials.

Secondary Data

Data is collected and recorded by someone else for their purposes but used by another researcher.

Characteristics:

1. Saves time and cost as the data already exists.

2. May lack relevance or reliability for the current study.

Sources of Secondary Data:

1. Published Sources:

• Government publications like the Census of India, Economic Surveys, and Reserve Bank reports.

• Trade journals, newspapers, magazines, and research articles.

2. Unpublished Sources:

• Data from private records, personal diaries, organizational documents, or unpublished government records.

Precautions While Using Secondary Data:

1. Check the source reliability to ensure authenticity.

2. Ensure the data is relevant to the current research problem.

3. Examine the data collection methodology used by the source.

Differences Between Primary and Secondary Data

Census and Sampling Methods

1. Census Method:

1. Data is collected from every individual or unit in the entire population.

2. Suitable for small populations or studies requiring complete accuracy.

3. Advantages:

i. Highly accurate and reliable.

Ii. Provides comprehensive information.

4. Disadvantages:

i. Expensive and time-consuming.

Ii. Not practical for large populations.

2. Sampling Method:

1. Data is collected from a representative subset (sample) of the population.

2. Types of Sampling:

1. Random Sampling:

1. Each unit of the population has an equal chance of being selected.

2. Example: Drawing lots or using random number generators.

2. Stratified Sampling:

1. The population is divided into subgroups (strata), and samples are taken from each group.

2. Example: Sampling urban and rural populations separately.

3. Systematic Sampling:

1. Units are selected at regular intervals from a list.

2. Example: Selecting every 10th student in a school.

3. Advantages of Sampling:

1. Saves time and resources.

2. Practical for large populations.

4. Disadvantages:

1. May introduce sampling errors.

2. Less reliable if the sample is not representative.

Methods of Data Collection

1. Direct Interview:

• Involves face-to-face interaction with respondents to gather detailed information.

• Example: Interviewing business owners about sales trends.

2. Telephone Surveys:

• Collecting data through phone calls, often used for quick surveys.

• Example: Telephonic feedback from customers.

3. Observation:

• Recording behavior or events directly without asking questions.

• Example: Observing traffic flow at an intersection.

4. Mail Questionnaire:

• Sending forms to respondents via mail for self-completion.

• Suitable for literate and geographically dispersed populations.

Errors in Data Collection

1. Sampling Errors:

• Errors that arise due to the method of sampling, such as selecting an unrepresentative sample.

• This can be minimized by using appropriate sampling techniques and increasing the sample size.

2. Non-sampling Errors:

• Errors occur during data collection, recording, or processing.

• Examples:

• Respondents providing false information.

• Misinterpretation of questions.

• Data entry mistakes.

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• Simplified explanations of primary and secondary data, making it easy to understand core concepts.

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• Highlighted key points and formulas essential for scoring well in exams.

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Conclusion

Mastering the concepts of data collection is vital for statistical analysis and economic studies. Vedantu’s CBSE Class 11 Chapter 2 - Collection of Data Notes simplifies these topics with comprehensive, student-friendly content. By bridging theoretical knowledge with practical applications, these notes empower students to excel in their academic journey. Download the FREE PDF today and elevate your understanding of this critical chapter!

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