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Computer Chapter 4 : Topic 2.4
Qualitative Data
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In a dataset containing students' blood groups, which type of categorical attribute is most appropriate for storing this information?
Reasoning: Blood groups are categories without any natural order, making them nominal.
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A survey records customer satisfaction as Poor, Fair, Good, and Excellent. This attribute is classified as:
Reasoning: The categories have a meaningful ranking from Poor to Excellent.
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Which of the following attributes is an example of a binary categorical attribute?
Reasoning: Binary attributes have only two possible categories.
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A school stores students' house names as Red, Blue, Green, and Yellow. These values represent which type of attribute?
Reasoning: House names are labels without any ranking or order.
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Which feature distinguishes an ordinal attribute from a nominal attribute?
Reasoning: Ordinal categories can be ranked, while nominal categories cannot.
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In an online shopping system, product ratings of 1 star to 5 stars are best classified as:
Reasoning: Ratings indicate an order from lower to higher satisfaction.
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A researcher wants to classify vehicles as Car, Bus, Motorcycle, and Truck. Which attribute type should be used?
Reasoning: Vehicle types are distinct categories with no natural order.
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A hospital database stores whether a patient has diabetes as "Yes" or "No." This is an example of:
Reasoning: Only two possible values exist: Yes or No.
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Which attribute would most likely be stored as an ordinal categorical attribute in a dataset?
Reasoning: Performance levels can be ranked from low to high.
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Which of the following examples best represents a nominal categorical attribute?
Reasoning: Marital status categories have no inherent ranking.
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If categories can be arranged from lowest to highest importance, the attribute should be classified as:
Reasoning: Ordered categories are characteristics of ordinal attributes.
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A binary attribute differs from other categorical attributes because it:
Reasoning: Binary attributes are limited to two distinct values.
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Which dataset attribute is most likely binary rather than nominal or ordinal?
Reasoning: Male/Female contains only two categories, fitting a binary attribute.
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Why is "Excellent, Good, Average, Poor" considered an ordinal attribute instead of nominal?
Reasoning: The categories can be logically ordered from best to worst.
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