Numeric or quantitative data attributes

The following are numeric or quantitative data attributes:

• These kinds of data attributes are numeric and represent a measurable quantity
• Examples: Financial data, population of a city, weight of people, and so on

There are two sub-types of numeric data attributes:

• Continuous data:
  • These kinds of data attributes are continuous
  • Examples: If you are recording the weight of a student, from 10 to 12 years of age, whatever data you collect about the student's weight is continuous data; Iris flower corpus
• Discrete data:
  • Discrete data can only take certain values
  • Examples: If you are rolling two dice, you can only have the resultant values of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 12; you never get 1 or 1.5 as a result if you are rolling two dice
  • Take another example: If you toss a coin, you will get either heads or tails

These kinds of data attributes are a major part of analytics applications.