DA0-001 · Question #221
A feature can take certain values (A, B, C, D, E, and F) and represents a grade of students from a college. Which of the following variables does this describe?
The correct answer is B. Ordinal variable. The grades A, B, C, D, E, and F represent an ordinal variable because they are distinct categories with a meaningful order or ranking, but the differences between categories are not necessarily uniform or quantifiable.
Question
A feature can take certain values (A, B, C, D, E, and F) and represents a grade of students from a college. Which of the following variables does this describe?
Options
- ADiscrete variable
- BOrdinal variable
- CNumerical variable
- DContinuous variable
How the community answered
(54 responses)- A2% (1)
- B91% (49)
- C6% (3)
- D2% (1)
Why each option
The grades A, B, C, D, E, and F represent an ordinal variable because they are distinct categories with a meaningful order or ranking, but the differences between categories are not necessarily uniform or quantifiable.
While grades are discrete in that they take specific, separate values, "discrete variable" is a broader term that applies to any countable variable. "Ordinal variable" is more specific and accurately captures the ranking aspect of grades.
An ordinal variable is a categorical variable where the categories have a natural, meaningful order or ranking, but the intervals between the ranks may not be equal or quantifiable. Student grades (A, B, C, etc.) clearly have a rank (A is better than B), but the "distance" between an A and a B might not be the same as between a C and a D.
A numerical variable, also known as a quantitative variable, represents measurable quantities, and grades (A, B, C, etc.) are categories, not direct numerical measurements themselves, even if they can be assigned numerical equivalents for calculation.
A continuous variable can take any value within a given range (e.g., height, temperature), which is not the case for distinct, ranked letter grades.
Concept tested: Data types - ordinal variables
Source: https://www.ibm.com/docs/en/spss-statistics/28.0.0?topic=values-measurement-levels-variables
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