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Data can be broadly classified under Textual data and Numeric Data as explained.
Data
Textual Numeric
Continuous Discrete
Nominal Data Ordinal Data
Textual Data (Qualitative Data)
Textual data is the information that is written or expressed using words and language. It includes things like
articles, books, emails, messages, and any other written content. Instead of numbers, it's made up of letters,
words, and sentences that convey meaning and information. Qualitative data is also called categorical data.
For example, "Learning AI is fun."
Qualitative data is further classified into two types that includes,
• Nominal data
• Ordinal data
Nominal Data
It consists of categories or names that cannot be ordered or ranked. Nominal data is often used to categorize
observations into groups, and the groups are not comparable. Examples of nominal data include gender (Male
or Female), and blood type (A, B, AB, O).
Ordinal Data
It consists of categories that can be ordered or ranked. Ordinal data is often used to measure opinions, where
there is a natural order to the responses. Examples of ordinal data include education level (Elementary, Middle,
High School, College), job position (Manager, Supervisor, Employee), etc.
Numeric Data (Quantitative Data)
Numeric data means information that's in numbers, not words or descriptions. It's often called quantitative data
because it's collected as numbers and can be used for math and stats. For instance, if you know the total number
of workers and how many are men, you can figure out how many are women by subtracting. This ability to do
calculations with numeric data makes it great for doing statistics and analysing data.
For example, marks, temperature, height, weight, etc.
Data Literacy 263

