A-Z Popular Blog Data Search »
Technology Guides

Continuous Data vs Discrete Data

 , updated on
Continuous data is information that can be measured at infinite points. Visually, this can be depicted as a smooth graph that gives a value for every point along an axis.
Discrete data is information that can be counted. This can be visually depicted as a bar chart.

Continuous vs Discrete

Continuous variables such as time, temperature and distance can theoretically be measured at infinitely small points. You can measure time every hour, minute or second. In theory, a second could be divided into infinite points in time.
Discrete variables are elements that can be counted such as people, buildings or money. Generally speaking, you can't divide a person, building or penny into smaller units. As such, they can only be counted one way.


Ocean currents are continuous data because they can be measured at infinite levels of detail at infinite points in time.
The test results of 300 students who write a multiple choice exam with 65 points is discrete because both students and points are counted with no measurements possible inbetween.
Continuous Data vs Discrete Data
Continuous Data
Discrete Data
Information that can be measured at infinite points.
Information that is counted.


This is the complete list of articles we have written about data.
Abstract Data
Atomic Data
Big Data
Cohort Analysis
Dark Data
Data Analysis
Data Architecture
Data Attribute
Data Cleansing
Data Collection
Data Complexity
Data Consumer
Data Control
Data Corruption
Data Custodian
Data Degradation
Data Dredging
Data Entity
Data Federation
Data Integration
Data Integrity
Data Liberation
Data Lineage
Data Literacy
Data Loss
Data Management
Data Massage
Data Migration
Data Mining
Data Owner
Data Producer
Data Quality
Data Remanence
Data Risks
Data Rot
Data Science
Data Security
Data States
Data Transformation
Data Uncertainty
Data Veracity
Data View
Data Virtualization
Data Volume
Data Wipe
Decision Support
Deep Magic
Empirical Evidence
Event Data
Hard Data
Information Assurance
Legacy Data
Machine Data
Market Research
Master Data
Misuse of Statistics
Personal Data
Personal Information
Predictive Analytics
Primary Data
Primary Research
Qualitative Data
Qualitative Info
Quantitative Data
Raw Data
Reference Data
Small Data
Soft Data
Source Data
Statistical Analysis
Statistical Population
Structured Data
Transaction Processing
Transactional Data
Types Of Data
Unstructured Data
If you enjoyed this page, please consider bookmarking Simplicable.


An overview of data with a list of examples.

Transactional Data

A definition of transactional data with examples.

Machine Data

The common types of machine data.

Qualitative Data

A definition of qualitative data with examples.

Data In Rest

A definition of data in rest with examples.

Data Degradation

The basic types of data degradation.

Data Volume

The definition of data volume with examples.

Data Uncertainty

A definition of data uncertainty with examples.

Data Infrastructure

The definition of data infrastructure with examples.

Qualitative Data vs Quantitative Data

The difference between qualitative data and quantitative data.

Types Of Data

The basic types of data.

Reference Data

A definition of reference data with examples.

Master Data

A definition of master data with examples.

Quantitative Data

The common types of quantitative data.

Atomic Data

A definition of atomic data with examples.

Source Data

The common types of source data.

Context Awareness

The common types of context awareness.

Raw Data

The definition of raw data with examples.

Data In Use

A definition of data in use with examples.
The most popular articles on Simplicable in the past day.

New Articles

Recent posts or updates on Simplicable.
Site Map