Lecture Notes on Collection of Data

Jul 27, 2024

Lecture Notes on Collection of Data

Introduction

  • Topic: Collection of Data (Chapter 2)
  • Previous chapters covered: Mean, Mode, Median, Correlation, Regression.
  • Focus: Quantitative data only (numerical, not qualitative).
  • Importance of data in statistics.

Data Types

1. Primary Data

  • Definition: Collected directly by the investigator for a specific purpose.
  • Example: Collecting names and phone numbers for a class trip.
  • Characteristics:
    • First-hand information.
    • Directly from the source of origin.

2. Secondary Data

  • Definition: Data collected previously for another purpose.
  • Example: Using a class list provided by a teacher.
  • Characteristics:
    • Already exists, collected by someone else.
    • Can be published or unpublished.

Distinction Between Primary and Secondary Data

Primary Data

  • Original, first-hand information.
  • Collected for a specific objective without adjustment.
  • Costly in terms of time and effort.

Secondary Data

  • May lack originality and accuracy.
  • Can be less costly and less time-consuming; involves use of existing data.
  • Adjustments might be needed to fit the current study’s objectives.

Methods of Collecting Primary Data

  1. Direct Personal Investigation

    • Face-to-face data collection.
    • Suitable for limited fields of investigation.
    • Merits: Originality, accuracy, reliability.
    • Demerits: Not practical for large groups, potential for personal bias.

  2. Indirect Oral Investigation

    • Collecting information from witnesses or individuals connected to the subject.
    • Merits: Useful for large investigations, free from personal bias of the investigator.
    • Demerits: Less accurate due to reliance on the informant's knowledge.

  3. Information From Local Sources or Correspondence

    • Local agents gather data and send it to a central office.
    • Merits: Economical and relevant for regular information.
    • Demerits: Less originality and accuracy due to multiple sources.

  4. Mailed Questionnaire

    • Sending questions by mail to collect responses.
    • Merits: Economical, allows data collection over a wide area.
    • Demerits: Limited use for uneducated individuals, possible lack of interest in completing the questionnaire.

  5. Schedules Filled Through Enumerators

    • Trained persons collect data through structured questioning.
    • Merits: High accuracy and completeness, less bias.
    • Demerits: Expensive and time-consuming due to the need for trained enumerators.

Qualities of a Good Questionnaire

  • Limited number of questions (focus on relevant information).
  • Simplicity and clarity in language.
  • Proper order of questions.
  • Avoidance of undesirable or sensitive topics.
  • Pre-testing of questions before full deployment.
  • Clear instructions for respondents.
  • Cross-verification questions for accuracy.

Methods of Collecting Secondary Data

  1. Published Sources
    • Government publications (e.g., census data, industry reports).
    • Semi-government and trade associations publications (e.g., reports from trade associations).
    • Research studies published in journals.
  2. Unpublished Sources
    • Data collected for internal use, may require access to organizational records.

Precautions in Use of Secondary Data

  • Assess the credibility of the data-collecting organization.
  • Confirm the objective and scope of the collected data aligns with current study needs.
  • Verify the collection method and its suitability.
  • Consider the time and context of data collection.
  • Ensure the units of measurement used are consistent.
  • Validate the accuracy of the numbers used.

Important Questions from the Chapter

  1. Distinguish between primary and secondary data.
  2. Explain the various methods for collecting primary data, along with their merits and demerits.
  3. Define secondary data and mention some sources.
  4. Discuss precautions to be taken when using secondary data.
  5. Define what makes a good questionnaire.

This concludes the lecture on "Collection of Data". Make sure to understand each section well, as these concepts will be crucial for exams and practical applications in statistics.