CompTIA Data+ (DA0-002)Data Concepts and EnvironmentsMedium
A data scientist is working with a dataset containing customer satisfaction scores on a scale of 1 to 5, where 1 is 'Very Dissatisfied' and 5 is 'Very Satisfied'. While the scores have an order, the difference between a score of 1 and 2 is not necessarily the same as the difference between 4 and 5 in terms of actual satisfaction. Which data type best describes these satisfaction scores?
- ARatio
- BNominal
- COrdinal
- DInterval
Show answer & explanationAnswer & explanation
Correct answer: C. Ordinal
Ordinal data has a meaningful order, but the intervals between values are not necessarily equal or measurable. Customer satisfaction scores on a scale of 1-5 have a clear order (1 is worse than 5), but the 'distance' between each score isn't uniform or quantifiable.
Why the other options are wrong
- A. Ratio data has a true zero point and equal intervals, which is not applicable to satisfaction scores.
- B. Nominal data has no inherent order, which is not true for satisfaction scores.
- D. Interval data has equal intervals, which is explicitly stated as not being the case here.
Ordinal Data
A type of qualitative (categorical) data that has a meaningful order or ranking among its categories, but the intervals between the values are not necessarily equal or quantifiable.
- Categories have a distinct order.
- Difference between categories is not quantifiable or uniform.
- Examples: satisfaction ratings (low, medium, high), education levels, survey scales.
Memory trick: Think 'Ordinal' for 'Order' – things you can rank but not precisely measure the distance between.