Q. What are the differences between nominal, ordinal, interval, and ratio data types?

Answer

Nominal and ratio data types are both used to describe categorical variables. The difference between the two data types is that ordinal data has ordered categories (class rank, socioeconomic status, Likert scales, etc.), and nominal data (gender, ethnicity, etc.) does not.

Interval and ratio data types are both used to describe numeric variables. The key difference is that ratio data has a “true zero”. In other words, a value of zero signifies that the variable you’re describing doesn’t exist. Weight is an example of ratio data because if an object weighs zero pounds, it is weightless. Temperature in degrees Fahrenheit is an example of interval data because a temperature of zero degrees just means it’s really cold, not that the temperature doesn’t exist. 

Evaluate the data type using the following tree diagram: 

 


The tree diagram helps us decipher what kind data types we are working with. If the data is categorical, you can ask yourself whether the order matters. If it does, then it is ordinal, if it does not, then it is nominal. If the data is numeric, you can ask yourself whether the value of 0 means the quantity does not exist. If it does mean this, then you are dealing with a ratio data type, if it does not, then you are dealing with an interval data type.





 

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  • Last Updated Apr 23, 2021
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  • Answered By Dorian Frampton

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