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What Is a Discrete Data Set?

When running an experiment or conducting a survey, you need to collect data to draw conclusions from your work. The data you collect can fall into one of two types, discrete or continuous. It is useful to know what type the data is so you can best analyze and present it.

Data
- Data is defined as facts or statistics brought together for reference or analysis. You may collect your own data, for example, by measuring variables in an experiment, or by recording characteristics of a set of objects or people. A data set is the list of measurements, or collection of recordings, you made. The number of measurements you make is known as the sample size of the data set.
Discrete Data
- There are two main types of data: discrete and continuous. The word "discrete" means separate and distinct. Discrete data has a finite number of natural categories, whereas continuous data can take an infinite number of values, and has no natural categories. The categories of discrete data do not overlap. Mathematically, the values of discrete data can take on separate, isolated points on the number line.
Examples of Discrete Data
- An example of discrete data is hair or eye color. In eye color, the categories may be blue, brown, green and hazel. An example of continuous data is height or weight, where no such categories exist. You can impose your own categories onto weight by putting each measurement into a range of weights. For example, these ranges may include 100 to 109 pounds and 110 to 119 pounds, turning it into a discrete data set. However, the natural way to express weight measurements is as a continuous data set.
Presenting and Analyzing Discrete Data
- Several ways of presenting data lend themselves to displaying discrete data, in particular. The simplest way is to list the data in a table with categories in one column and number of occurrences, or frequency, in the next column. A simple analysis you can perform is to calculate the percentage of the total frequency that each category makes up. Do this by adding up each frequency to find the total, and dividing the frequency for each category by the total frequency. Multiply the result by 100 to find the percentage.
  
  Bar charts are a more visually stimulating method for presenting a discrete data set, where each category has its own bar on the x-axis of the graph, and the frequency of each category on the y-axis.

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