Data can be classified into different types based on its nature and characteristics. The main types are qualitative data, which represents categories like gender or satisfaction ratings, and quantitative data, which consists of numerical values that can be measured. Data can also be primary, collected directly from sources, secondary, collected by others, raw, unprocessed, or processed, cleaned and analyzed. Qualitative data describes qualities while quantitative data represents quantities numerically.

1. DATA AND IT’STYPES
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Data refers to a collection of facts, figures, or information that can be used for analysis,
interpretation, and decision-making.
Data is typically classified into different types based on its nature and characteristics.
The main types of data are:
1. Qualitative Data (Categorical Data): This type of data represents categories
or labels and cannot be measured in numerical terms.
Examples include:
a. Nominal Data: Categories with no inherent order or ranking (e.g., colors,
gender).
b. Ordinal Data: Categories with a meaningful order or ranking (e.g., education
levels, customer satisfaction ratings).
2. Quantitative Data (Numerical Data): This type of data consists of numerical
values that can be measured and subjected to mathematical operations.
Examples include:
a. Discrete Data: Numerical values that are distinct and separate, often counted
in whole numbers (e.g., number of employees, items sold).
b. Continuous Data: Numerical values that can take any value within a range and
can be measured with great precision (e.g., height, weight, temperature).
1. Primary Data: Data collected directly from sources through methods like
surveys, experiments, interviews, or observations.
2. Secondary Data: Data that has been collected and processed by someone else
and is used by researchers for their purposes. This can include data from
government sources, academic publications, or other research studies.
3. Raw Data: Unprocessed and unorganized data that is directly collected from
sources.
4. Processed Data: Data that has been cleaned, organized, and analysed to extract
meaningful insights.
• Qualitative vs. Quantitative Data: Qualitative data describes qualities or
characteristics and is non-numeric, while quantitative data represents quantities
and is numeric.