D A T A

Chapter 2 of the sources, titled Data, focuses on defining what data is and providing a framework for how it is organised, classified, and measured. Data are defined as the facts and figures collected, analysed, and summarised for the purpose of presentation and interpretation.

1. Unstructured vs. Structured Data

The sources first distinguish between how data is organised:

2. Variables and Cases

Within structured data tables, two components are essential:

• Case (Observation): The individual unit for which data is collected , uniquely identifying each row.

• Variable: A characteristic or attribute that varies across different units , typically represented by the columns.

  
  Example: In a student table, each student (Anjali, Pradeep) is a case, while their “Gender” or “Marks” are variables.

3. Classification of Data

Data is broadly classified into two categories:

4. Time-Series vs. Cross-Sectional Data

This distinction depends on when and where the data is recorded:

5. Scales of Measurement

There are four levels of measurement used to collect data:

1. Nominal: Labels or names used to identify characteristics with no inherent order.
   • Example: Blood group, Hair colour, or Brand names.
2. Ordinal: Labels where the order or rank is meaningful, but the exact distance between values is not fixed.
   • Example: Service ratings such as “Excellent,” “Good,” and “Poor”.
3. Interval: Numeric data where the interval between values is fixed, but there is no absolute zero. Ratios are meaningless here because zero is arbitrary.
   • Example: Temperature in Celsius or Fahrenheit (0°C does not mean “no temperature”).
4. Ratio: Numeric data with all the properties of interval data plus an absolute zero. Ratios between values are meaningful.
   • Example: Height, Weight, and Marks.

Practice Questions