Variable vs. Attribute Data: What’s the Difference?

Variable vs. Attribute Data: What’s the Difference?

What is Variable Data?

Variable data is any kind of information that is represented and recorded as measurements. The term is often used when discussing the creation of control charts for the purpose of process analysis. Variable data is quantitative, which means it can be described with numerical value and can change along a perpetual scale. This kind of data includes things like length in inches, temperature in degrees or weight in pounds.

The Benefits of Variable Data

This kind of information is useful for control charts, but it’s also an essential element of business analysis beyond this purpose. It is well-suited for more advanced analytical techniques and mathematical operations, which means it can be manipulated and strategically used by statisticians and data scientists.

How to Create Variable Data

The way data is collected, organized and presented has profound implications for the end results. Creating variable data is a simple matter of using uniform and scaled measurements to assess product or process state. In short, measure everything with a solid standard and units.


What is Attribute Data?

Attribute data is more qualitative, which means it focuses on how individual items relate to general requirements. Attribute data can often be boiled down to a “yes or no” question. Either a product or process meets a certain standard or it does not. For example, when sitting down a chair will either support the person or break. Attribute data describes the capability of the chair to meet the demands placed on it.

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The Benefits of Attribute Data

While it’s not as useful in more complex calculations, there are plenty of reasons why attribute data is an important tool. Since it’s already confined to discrete categories, this kind of information is already relevant and easy to understand. It also helps keep the issues clear and keep the focus on how the data points connect to real life.

How to Create Attribute Data

Collecting attribute data is usually a matter of asking the right questions. Does a cup hold water or does it leak? Is there enough gas in the car to get to work? Can this product perform its basic features to minimum specifications?

Attribute data is all about assessing the specific capabilities of the object in question. What capabilities you care about and what counts as a success depends on the demands of the situation. That’s why analysts need to be careful and thorough when setting up this kind of study.


Variable vs Attribute Data: What’s the Difference?

The differences between attribute and variable data are mostly in details and presentation. Attribute data can show if something failed or not, while variable data can show how much it failed by. It’s not just about being more detailed though.

Variable data is collected through objective measurement and is oriented around the dimensions, characteristics or features of the subject. Attribute data is only centered around the utility, benefit or capability of the subject.

Variable and Attribute Data: Who would use Variable Data and Attribute Data?

Business leaders that embrace Six Sigma practices need to learn about control charts and the basic elements needed to create them. Companies should really use both kinds of data on a regular basis as basic material for their statistical analysis and as starting points for discussion about strategic development.

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However, choosing one type of data over the other for a specific situation depends on the goals. Generally, analysts focus on attribute data when they want to examine many different types of products or processes and how they relate to the larger operation. Variable data is preferred when examining the state of products or processes individually to find ways to improve them.

Choosing Between Variable and Attribute Data: Real World Scenarios

A popular amusement park has roller coasters and rides for children of all ages. Due to the large target age range, there are quite a few rides in the park that have minimum and maximum sizes. This means the park has to gather data about every customer before they get on these age restricted rides.

If the park measured each child’s height when they walked into the park, that would be considered variable data. However, checking if a child is above the “Must be taller than this to ride” sign would be attribute data. Variable data is an objective measurement of the child’s height and attribute data is from the relative comparison of being able to get on the ride or not.

Take control with data

Data is only a dry subject until you see it in action. Understanding how to harness the power of information is a powerful asset for any business leader and it’s certainly a boon to their companies. Take the time to learn about statistics and data science because they are handrails on the stairs to efficient and lean management practices.

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