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Quantitative data can be broken down into discrete and continuous data.
Discrete data is data that can be counted, such as the number of heads in 100 coin flips and the number of books in a library. If you can count it, it is discrete!
Continuous data is data that cannot be counted, but can be measured, such as a person's height, a dog's weight, and the time of a marathon run. Continuous data can be further broken down into interval and ratio data. Interval data is comprised of ordered units with the same difference between units, such as in the following list of values: -15, -10, -5, 0, 5, 10, 15. Further examples include credit scores (300-850), pH, and temperature in Fahrenheit. Here, we can add and subject in meaningful ways, and there is no "true" zero. In interval data, the "zero" is arbitrary.
Ratio data as a natural zero quantity of a thing being measured, such as weight, length, and temperature in Kelvin. When the variable equals 0, there is none of that variable.
Survey Methodology and Missing Data: Tools and Techniques for Practitioners by 
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