Discrete data is a set of data having a finite entire number of entire or undivided value or data points (Sekaran, 2003). For example: the number of passengers in a plane where it is impossible to divide a passenger in half or quarters. In the opposite way, Continuous data makes up the rest of numerical data. This is a type of data that is usually associated with some sort of physical measurement (Sekaran, 2003). For example: the lifetime of a tire, could it take 30,000 miles? How about 32,000.7 miles? Or 42,7279 miles? One common way to tell if data is continuous is asking if it is possible for the data to take on values that are decimals or fractions; if the answer is yes, this is typically continuous data.

One of the features of discrete data is that it can be analyzed using a normal distribution. Discrete data can be analyzed using a normal distribution using approximation and deal with it as continuous. The difficulty is to find the probability of an event as a single value.

**Reference:**

Sekaran, U. (2003). *Research methods for business: A skill-building approach* (4th ed.). New York, NY: John Wiley & Sons.