Sources, Acquisition, and Classification

Data is raw, unorganized facts that need to be processed. Information is data that has been processed, organized, or structured in a given context to make it useful. Before one can interpret data, one must understand where it comes from and how it is categorized.

1. Sources and Acquisition of Data

Data acquisition is the process of sampling signals that measure real-world physical conditions and converting the resulting samples into digital numeric values. In research, data is broadly acquired from two sources (Kothari, 2004):

• Primary Data: Data collected firsthand by the researcher for the specific purpose of the study. It is original in character.
  • Examples: Surveys, questionnaires, direct observations, focus groups, and controlled experiments.
• Secondary Data: Data that has already been collected by someone else and has passed through the statistical process.
  • Examples: Government census reports, academic journals, historical records, and published books.

2. Classification of Data

Once acquired, data is classified based on its nature into two fundamental branches: Qualitative and Quantitative.

Qualitative Data (Categorical)

Deals with descriptions and traits that cannot be easily measured mathematically. It is subdivided into:

• Nominal Data: Data used to name or label variables without any quantitative value or intrinsic ordering. E.g., Hair color (Blonde, Brown, Black), Blood Type (A, B, O).
• Ordinal Data: Data that has a natural order or ranking, but the exact differences between the ranks cannot be quantified. E.g., Customer satisfaction ratings (Poor, Fair, Good, Excellent), socioeconomic status (Low, Middle, High).

Quantitative Data (Numerical)

Deals with numbers and things that can be measured objectively. It is subdivided into:

• Discrete Data: Information that can only take on certain, specific, distinct values (often whole numbers). It is counted. E.g., The number of students in a class, the number of cars in a parking lot.
• Continuous Data: Information that can take any value within a range (including fractions and decimals). It is measured. E.g., The exact weight of a student (65.43 kg), the temperature of a room, time taken to finish a race.