Understanding Discrete vs. Continuous Data and Uses for Each

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To understand the basics of discrete and continuous data, it’s necessary to be familiar with the main differences between them.

1. Discrete Data Are Whole Numbers, Whereas Continuous Data Can Be Fractions or Decimals.

Discrete data points are distinct, separate and countable, while continuous data points are part of a continuous spectrum. Before collecting and analyzing data, you will have to determine how precise you need the figures to be. That will determine which type of data you use.

2. Continuous Data Is More Precise.

Since continuous data allows for fractions or decimals, it enables you to measure something down to a very specific figure. Discrete data, on the other hand, provides less precision since it deals only with whole numbers or distinct categories.

3. Discrete Data Visualization Might Use a Bar Graph, Whereas Continuous Data Might Use a Line Graph.

To represent discrete data, people often use bar graphs, histograms or other methods that will show the frequency of the different categories or values. By comparison, people use line graphs to represent continuous data and show how the data points change continuously over a given range.

4. Scientific Research Is More Likely To Use Continuous Data.

Fields that require very precise measurements, such as engineering, medicine and quality control, gravitate toward continuous data and the detailed information that continuous data provides.

In fields where counting and categorization are important, however, people rely more on discrete data for work on things like inventory management, demographics or survey responses.

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