Attribute vs Variable data | Discrete vs Continuous data

→ The difference between attribute and variable data are mentioned below:
→ The Control Chart Type selection and Measurement System Analysis Study to be performed is decided based on the types of collected data either attribute (discrete) or variable (continuous).
→ This data can be used to create many different charts for process capability study analysis.
→ It plays a very important role as a part of the Problem Solving Process.

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What is attribute data?

→ It is qualitative data that can be counted or can be said as yes or no for recording and analysis.
→ The attribute is also called the "discrete" type and focuses on numbers.
→ It has two types: (1) Yes/No type (2) Counting type (i.e. no. of pieces, parts, or products)
→ For one item, there are only two possible outcomes: either it passes or it fails against the specification.
→ Each item inspected is either defective or not defective.
→ For example, suppose we are collecting data on defective products at our assembly line so the data simply classifies as defective or not defective.
→ A discrete data set is very simple to collect as compared to continuous data.

Examples of the Attribute data:

[01] Yes/No Type:
→ Mail delivered: is it on time or not on time?
→ The phone answered: is it answered or not answered?
→ Warehouse regular stock item: is it in stock or not in stock?
→ The invoice generated: is it correct or not correct?
→ Product confirmation: is it in-spec or out-of-spec?
→ The salesperson close the deal or did not?

[02] Count Type:
→ Number of defective products per shift
→ How many students have passed the exam?

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What is Variable Data?

→ It is observed or measured to any decimal place you want (if your measurement system allows it) and it is also called the "continuous" type.
→ For example, as per the sampling inspection plan, we are taking one sample out of 10 parts and checking the weight of it. So the reading should be in digits or numbers and variables like 250, 255, 248 grams, etc.
→ continuous data can tell us many things that discrete can not.
→ Suppose we are developing any new gear for an electric drive then attribute data tell us whether that is gear fixed with the drive or not? but with the help of variable data, we can check the performances of gear in various loading conditions and we can define the safe working load.