Data can be broadly categorized into two types:

• Discrete (or categorical): Any value that denotes a category is considered a discrete variable. Examples of discrete variables include most nouns such as fruits, colors, school grades, countries and genders.
• Continuous (or quantitative): Continuous numbers are numerical quantities on which you can perform arithmetic operations. This includes variables such as weather, temperatures, amounts, and time.

You may also hear of a couple of other variations of data types, which are but sub-categories of either discrete or continuous variables, as follows:

• Ordinal (discrete variable): This indicates data that has an order. For example, if we were to rank scores as first, second, and third denoting the top three scores, the numbers one to three are ordinal as they denote an order. They are not considered continuous.
• Nominal (discrete variable): This indicates data that does not have any inherent order, that is, which are not ordinal, for example, Male = 1 and Female = 2. These are not ordinal since there is no inherent order, but they are nominal in the sense that they denote a naming convention: