A Complete Overview Of Discrete Data In Quality

The term "discrete data" refers to countable, distinct items. These entities cannot be divided. They only exist in predetermined increments or units. There are a finite number of potential values for discrete variables. In other words, they have a limited number of intervals or categorical values. The fact that discrete data is "countable" as opposed to "measurable" is a significant feature of this type of data.

Frequently bar graphs and other non-persistent techniques are used to illustrate discrete data.

Numerous different types of data can be categorized as discrete data. For instance, it handles ordinal data, such as sliding scales (i.e., "bad, neutral, excellent"). Discrete data can be also used to quantify qualitative data. For example: finding the number of yellow vehicles on the road.

Features Of Discrete Data:

Discrete data is simple in statistical analysis and easy to compute.
Discrete Data can be finite, non-negative, and countable integers.
The data can be easily demonstrated using bar charts, pie charts, and line charts.
It is impossible to divide into parts.
Discrete data cannot be decimal values.
Discrete data can also be categorical containing a finite no of values.
It is distributed in terms of time and space.