Data types

There are a few different types of data – each reflecting the type of information that is stored. Understanding the differences is vital to dealing with the downstream effects of working with each type. The different data types are introduced as follows:

• Categorical: Nominal: Qualitative and with no ordering to the labels. For example, hair color (black, brown, blonde, and red).
• Categorical: Ordinal: Qualitative and ordered in some way. For example, satisfaction levels (not, somewhat, neutral, and very).
• Numerical: Discrete: Quantitative and with a finite sample space and/or countable infinite discretizations. For example, 1, 2, and 3. 
• Numerical: Continuous: Quantitative and covering an interval or span of real numbers. For example, all real numbers that span (3.0 - 5.0).