3. Basics of data literacy
The chapter provides an introduction to the fundamentals of data literacy, covering the definition of data, its various types, sources, collection methods, and storage solutions. It highlights the importance of data in decision-making, analysis, and ethical considerations surrounding data privacy. Understanding how to effectively represent, analyze, and interpret data lays the groundwork for future studies in artificial intelligence and data science.
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What we have learnt
- Data is defined as facts or figures collected for reference or analysis.
- There are various types of data: structured, unstructured, and semi-structured.
- Data plays a crucial role in informed decision-making and must be handled with ethical considerations.
Key Concepts
- -- Structured Data
- Organized data that can easily be searched in databases or spreadsheets, such as student records.
- -- Unstructured Data
- Data that does not have a predefined format, including emails and social media posts.
- -- Data Privacy
- The safeguarding of personal data to prevent unauthorized access.
- -- Data Representation
- The method of presenting data in formats such as tables, charts, and infographics to facilitate analysis.
- -- Data Ethics
- Guidelines that govern the responsible use of data to avoid harm or discrimination.
Additional Learning Materials
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