Data is any collection of information that can be used to improve decision-making. In business, data is used to measure performance, assess risk, and make strategic decisions. Data can be used to improve the effectiveness of marketing, operations, and financial management.
There are four types of data that are used extensively in statistics: categorical, quantitative, ordinal, and interval. Each type of data has its own unique properties that dictate how it can and should be used.
Data Management Solutions
Before getting into the four types of data and how to use them, it’s important to learn about data management. If you’re thinking to yourself, “What is data management?” It involves the accessibility, delivery, governance, and security of data to meet company objectives. There are many reasons to use data management in your business. Perhaps the most important reason is that it helps you make better decisions.
With accurate and up-to-date data, you can see what is working and what is not, and adjust your strategies accordingly. Data management also helps you identify trends and correlations, so you can anticipate changes in the market and adapt quickly. Additionally, data management can help you improve customer service and satisfaction, as you will have a better understanding of what your customers want and need. Ultimately, data management makes your business more efficient and successful. A data management platform allows for better access, trust, and control. Below, you’ll find the four data types and how to use them.
Categorical data is data that is divided into groups or categories. For example, sex (male or female), political party (Democrat or Republican), or eye color (blue or brown) are all examples of categorical data. Categorical data is usually displayed in a table or a graph with the categories as the rows or the columns.
Categorical data can be used to create pie charts and bar graphs. Pie charts are often graphical displays of categorical data in the shape resembling a pie. Each slice indicates the different categories. Bar graphs can indicate each category per column.
Quantitative data is data that is measured on a scale. For example, the number of people in a room, the amount of money in a bank account, or the temperature outside are all examples of quantitative data. Quantitative data is usually displayed on a table or a graph with the numbers on the scale as the rows or the columns.
Ordinal data is data that is measured on a scale, but the intervals between the numbers are not known. For example, the rank of a person in a class (first, second, third, etc.), the order of arrival of a race (first, second, third, etc.), or the severity of a crime (misdemeanor, felony, capital felony) are all examples of ordinal data.
Ordinal data is usually displayed in a table or a graph with the numbers on the scale as the rows or the columns, and the order of the categories as the labels. This data is ranked in order of importance. This is a lot like the results of a survey where people are asked to rate something on a scale from 1 to 10.
Interval data is data that is measured on a scale and the intervals between the numbers are known. For example, the time it takes for a person to run a mile, the age of a person, or the number of miles a car can travel before it needs to be refueled are all examples of interval data. Interval data is usually displayed in a table or a graph with the numbers on the scale as the rows or the columns, and the intervals between the numbers as the labels.
You can utilize these types to gain a clear understanding of all collected information in order to improve business operations.