Classify the following attributes as discrete, ordinal or continuous:number of "likes" on a photo student ID number education levels

To classify the given attributes, we need to understand the definitions of discrete, ordinal, and continuous data types:

1. Discrete: This type of data takes on a finite number of values. It usually represents countable items.
2. Ordinal: This type of data represents categories with a meaningful order but does not have consistent intervals between them.
3. Continuous: This type of data can take on any value within a given range and usually represents measurable quantities.

Classification of Attributes

1. Number of "likes" on a photo: This attribute is discrete because it refers to countable instances of likes and cannot take fractional values (e.g., you can have 10 likes, but not 10.5).

2. Student ID number: This attribute is discrete as well because it is a finite identifier assigned to each student and represents a countable value; although it can be viewed as categorical (identifying individuals), it does not represent a measurable quantity.

3. Education levels: This attribute is ordinal because it represents categories (e.g., high school, bachelor's, master's) that have a meaningful order but do not have consistent intervals between them. For example, the difference in level between high school and bachelor's may not be numerically consistent with the difference between bachelor's and master's.

Summary of Classifications

• Number of "likes" on a photo: Discrete
• Student ID number: Discrete
• Education levels: Ordinal