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Variables Data, Attributes Data, and Process Variation

A free online reference for statistical process control, process capability analysis, measurement systems analysis,
control chart interpretation, and other quality metrics.

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Variables data (measurements)

What is it?

Variables data is data that is acquired through measurements, such as length, time, diameter, strength, weight, temperature, density, thickness, pressure, and height. With variables data, you can decide the measurement’s degree of accuracy. For example, you can measure an item to the nearest centimeter, millimeter, or micron.

How is it used?

Variables data is normally analyzed in pairs of charts which present data in terms of location or central location and spread. Location, usually the top chart, shows data in relation to the process average. It is presented in X-bar, individuals, or median charts. Spread, usually the bottom chart, looks at piece-by-piece variation. Range, sigma, and moving range charts are used to illustrate process spread. Another aspect of these variables control charts is that the sample size is generally constant.

Use the following types of charts and analysis to study variables data:

These charts, and more, can be created easily using software packages such as SQCpack.

Additional reference material

Additional sections from legacy attributes-data-counts:

Attributes data (counts)

What is it?

Attributes data is data that can be classified and counted. There are two types of attributes data: counts of defects per item or group of items (nonconformities ) and counts of defective items (nonconforming).

How is it used?

Attributes data is analyzed in control charts that show how a system changes over time. There are two chart options for each type of attributes data. These attributes control charts, and more, can be created easily using software packages such as SQCpack.

What type of attributes data do I have?

Counts of defective items (noncomforming)

What is it?

Nonconforming data is a count of defective units. It is often described as go/no go, pass/fail, or yes/no, since there are only two possible outcomes to any given check. It is also referred to as a count of defective or rejected units. For example, a light bulb either works or it does not. Track either the number failing or the number passing.

How is it used?

Nonconforming data is analyzed in p-charts and np-charts. Chart selection is based on the consistency of the subgroup size:

  • If the number inspected is always or usually the same, use an np-chart.
  • If the number inspected varies with each subgroup use a p-chart.

Count of defects per item (noncomformities)

What is it?

Nonconformities data is a count of defects per unit or group of units. Nonconformities can refer to defects or occurrences that should not be present but are. It also refers to any characteristic that should be present but is not. Examples of nonconformities are dents, scratches, bubbles, cracks, and missing buttons.

How is it used?

Nonconformities data is analyzed in u-charts and c-charts. Chart selection is based on the consistency of the subgroup size:

  • If the number inspected is always or usually the same, use a c-chart.
  • If the number inspected varies with each subgroup use a u-chart.

What type of attributes data do I have?

Counts of defective items (noncomforming)

What is it?

Nonconforming data is a count of defective units. It is often described as go/no go, pass/fail, or yes/no, since there are only two possible outcomes to any given check. It is also referred to as a count of defective or rejected units. For example, a light bulb either works or it does not. Track either the number failing or the number passing.

How is it used?

Nonconforming data is analyzed in p-charts and np-charts. Chart selection is based on the consistency of the subgroup size:

  • If the number inspected is always or usually the same, use an np-chart.
  • If the number inspected varies with each subgroup use a p-chart.

Count of defects per item (noncomformities)

What is it?

Nonconformities data is a count of defects per unit or group of units. Nonconformities can refer to defects or occurrences that should not be present but are. It also refers to any characteristic that should be present but is not. Examples of nonconformities are dents, scratches, bubbles, cracks, and missing buttons.

How is it used?

Nonconformities data is analyzed in u-charts and c-charts. Chart selection is based on the consistency of the subgroup size:

  • If the number inspected is always or usually the same, use a c-chart.
  • If the number inspected varies with each subgroup use a u-chart.

Counts of defective items (noncomforming)

Count of defects per item (noncomformities)

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