What is the difference between variable and attribute data

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Do you need to supply an image an alt attribute if used witin a figure with a figcaption? Variable data can be used to create average X-bar charts, range charts, and sample standard deviation charts or "S-charts.

When constructing a control chart to map out variances in measurement data, companies and teams must collect both attribute and variable data as a part of the problem-solving process. Because the level of sensitivity of a measurement depends on the precision of the measuring device, there are times when variable data can be treated as attribute data.

For example, a company produces aluminum pins that may be smaller than 1. Rather than measuring each pin or even a sample of pins, one can:. Thus, treating the variable as an attribute offers an efficient way to determine if the pin will be effective. If you're practicing the Six Sigma approach and you want to see how many products meet your high standards, attribute data might do the trick.

If you want to measure the quality of each product, variable data is probably more useful. There are other ways to classify data. Data that doesn't adapt well to numbers, such as color or taste, is called qualitative data, for instance. Attribute data is simpler to gather than qualitative data, so it's a good choice if you're looking at a binary condition, where there are just two alternatives:.

You can compile the attribute data to see how well your process, equipment or staff are performing. If you want 80 percent of your students to pass their final exams, and only 20 percent do, that shows a problem. Whether it's the student body, the teachers or some other issue will have to be determined. Being able to perform mathematical operations on the data is what sets variable data from attribute data.

On the contrary, you cannot perform any mathematical operations nor do any kinds of analysis on attribute data. Attribute data can only be counted or can be said yes or no to. In quality control, a product goes for inspection can be either defective or not. There are only two possible outcomes for a product. Attribute data can be categorized as count type and yes or no type. Examples of variable data include the temperature reading in a mercury thermometer, GPA scores of all the students in a school, the amount of money you spend on shopping, the gas mileage of your car, the density of the liquid, height of a pillar, length of a road, or anything that has a value.

In a nutshell, variable data is data in which quality is described quantitatively in terms of dimensions, weights, or other characteristics whereas attribute data qualitative data that have a quality characteristic or attribute that is described in terms of measurements.

Variable data are more flexible because you can perform mathematical operations of the data in order to perform a more thorough analysis on the data. Variables usually require smaller samples than attributes. Difference Between Variable and Attribute.

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