Understanding the Basics of Data

Aug 13, 2024

Lecture on Data: A Primer

Introduction

  • Data holds different meanings for different people.
  • Objective: Provide a basic understanding of what "data" means.

Definition of Data

  • "Data" refers to facts of transactions or events.
  • Plural Form: Data is plural (e.g., "data are"), singular is "datum."
  • Common usage treats "data" as singular (acceptable in general use).

Importance of Data Quality and Integrity

  • Garbage In, Garbage Out: Poor quality data leads to unreliable findings.
  • High Integrity: Ensures meaningful analysis and interpretation.
    • Requires good measurement and data acquisition.
    • Post-processing structure application is crucial.

Errors Affecting Data Quality

  • Common errors:
    • Transcription
    • Transposition
    • Lack of validation
    • Joining errors
    • Human errors
  • Focus: Clean and structure data to maintain integrity and quality.

Types of Data

Qualitative Data

  • Rich descriptions (e.g., text, photos, sound recordings).
  • Analysis Methods: Thematic analysis, content analysis.

Quantitative Data

  • Numeric properties, can be counted and analyzed.
  • Analysis Methods: Descriptive and inferential statistics.

Transition Between Data Types

  • Qualitative data can transition to quantitative through numeric application.
  • Example: Employee performance evaluations with both narrative and numeric ratings.
    • Qualitative: "John completes reports in a timely manner..."
    • Quantitative: Numeric scores (e.g., 3.9, 4.4, 4.2).
  • Employee surveys using Likert scales to quantify satisfaction.

Interpretation of Data

  • Data Don’t Speak: Requires human interpretation.
  • John Matthew Quote: Highlights the importance of interpretation.

Data, Information, and Knowledge

  • Data: Basic facts (e.g., list of ages).
  • Information: Interpreted data with a goal (e.g., average age).
  • Knowledge: Information with applied meaning (e.g., recruitment planning based on average age).

Conclusion

  • Purpose of lecture: A crash course on data and its fundamental meaning.
  • Emphasis on understanding, quality, and practical application of data.
  • End of Lecture: Thank you for your attention.