Which of the following best describe qualitative data?

Qualitative data refers to non-numeric information that describes qualities or characteristics. It is often categorized based on attributes or properties and is typically descriptive in nature.

Ordinal Data:This type of qualitative data represents categories with a meaningful order but without a consistent interval between them. Examples include rankings (e.g., customer satisfaction levels such as 'satisfied,' 'neutral,' 'dissatisfied') where the order matters, but the difference between ranks is not uniform.

Nominal Data:This qualitative data type consists of categories without any inherent order. Examples include gender, race, or types of products. Each category is distinct, and there is no logical sequence.

In contrast, options A (Discrete) and D (Continuous) refer to quantitative data types:

Discrete Data:Quantitative data that can take on only specific, distinct values (e.g., the number of students in a class).

Continuous Data:Quantitative data that can take on any value within a range (e.g., height, weight).

Options C (Batch) and F (Real-time) pertain to data processing methods rather than data types.