Classificationof data (1)�

Quantitative Data: 

Data that can be measured numerically. 

Examples: Height, weight, age, or the number of bacteria colonies on a plate. 

Qualitative Data

Data that represents categories or qualities and cannot be measured numerically. 

Examples: Gender, eye color, stage of a disease (e.g., I, II, III, IV), or blood type

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Quantitative Data

• Quantitative data is information that can be measured, counted, and expressed in numerical values.
• It is used to answer questions like "how many?" or "how much?" and can be analyzed statistically to find patterns, trends, and relationships

Qualitative Data

• Nominal Data: Data that can only be categorized into names or labels without an inherent order or rank

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• Ordinal Data: Data with categories that have a natural, meaningful order or ranking, but the differences (intervals) between the values are not quantifiable or necessarily equal.

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Quantitative Data

• Discrete Data: Data that can only take on distinct, separate values, typically whole numbers, obtained by counting.

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• Continuous Data: Data that can assume any value within a specific range or interval and can be infinitely subdivided into finer levels of precision, obtained by measurement.

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Interval scale

• Definition: A quantitative measurement scale with a meaningful order and equal intervals between values, but without a true zero point

Ratio scale

• Definition: A quantitative measurement scale that has all the properties of an interval scale, plus a true zero point that indicates the absence of the variable being measured