Many businesses use quantitative data to assess the performance of their products and departments. Quantitative data can be measured in many ways, including discrete and continuous data. Understanding the differences between these data types and how they are collected and analyzed can help businesses make better decisions.
Examples of discrete data
Businesses track discrete data for a variety of information. Here are some examples discrete data that you could track for a business:
Tickets are on sale
A common example of discrete information is the number of tickets sold on a particular day. The number of tickets sold allows a business prepare for the right number of visitors or attendees. The number of tickets sold is discrete information because it doesn’t change when the company stops selling them.
Number of employees
Another discrete type of data is the number of employees in a business. The number of employees is important to companies because it helps them achieve their growth goals. Some companies maintain a certain ratio between management and lower-level staff to ensure that every employee gets guidance and direction.
The number of product reviews
Another example of discrete information is the number of product reviews received by a company in a certain time period, like a week. If companies want to know how their customers feel about their products, they may give consumers the option of leaving reviews. When analyzing customer satisfaction, it is useful to track the number of reviews that a product has received.
Employee hire dates
Many companies track the dates of their employees’ hiring. Onboarding is often preceded by a short training period. The manager can determine the current training stage by recording how long an employee has been with a company. The date of an employee’s hiring can also help determine when employee benefits such as health insurance become active.
Discrete data vs. continuous data
Quantitative data can be either discrete or continuous. The type of information that they represent is what makes them different. Continuous data can show data trends over time, while discrete data only shows information about a specific event. Other differences between discrete and continuous data are:
- Values: You can count discrete data, like the number of students. Continuous data, on the other hand, often contains measurable values that represent a variety of information. For example, the height difference between the tallest and shortest student in a classroom.
- Data types: Discrete values are usually integers, or whole numbers. Data values for continuous data are often fractions or decimal places.
- Methods: Usually, discrete data can be measured using simple methods such as a bar chart or number line. For continuous data you can use more complicated methods, like curves or histograms.
- Time intervals: Distinctive data is usually constant over a certain time interval, while continuous data can have different values over time.
Discrete/continuous data visualization
It is important to understand the performance of an organization by visualizing discrete or continuous data. Here are some ways to represent this type data:
A graph is one way to visually represent quantitative data. Businesses often use bar graphs to chart discrete data.
The bar graph can be used to show data for specific categories. For example, the sales figures of five employees in May. Bar graphs can be useful when plotting discrete information because they let you compare differences between data points.
A histogram is similar to a bar chart, except that it groups the data into specific values. A histogram is often used to show trends in continuous data. A histogram can show, for example, the average wait time of a customer to speak to a representative in a call centre. Each bar in the histogram can represent a specific time period, for example 30-60 seconds.
A frequency table is an easy chart with a side for each category and another side for the numerical value. A company may label a table “Menu Items Sold Today” by putting the name of an item on one side, and the number sold on the opposite side. Frequency charts can help you visualize the trends of popular items.
A plotted point graph is a graph that has an x and ay axis. You can freely plot discrete data or continuous data on this graph to show trends in data with a small or large number of variables. This type of graph can help you quickly view data, which is useful when you are trying to understand trends.