Variables control charts plot continuous measurement process data, such as length or pressure, in a time-ordered sequence. In contrast, attribute control charts plot count data, such as the number of defects or defective units. Variables control charts, like all control charts, help you identify causes of variation to investigate, so that you can adjust your process without over-controlling it.

There are two main types of variables control charts: charts for data collected in subgroups and charts for individual measurements.

Each point on the graph represents a subgroup; that is, a group of units produced under the same set of conditions. For example, you want to chart a particular measurement from your process. If you collect and measure five parts every hour, your subgroup size would be 5.

Variables control charts for subgroups include Xbar, R, S, and Zone.

Minitab also offers several combination charts for subgroups: Xbar-R, Xbar-S, I-MR-R/S (between/within). Use these to view both the process mean and the process variation at the same time.

Each point on the graph represents an individual measurement; thus, the subgroup size is 1. Individuals charts are used when measurements are expensive, production volume is low, or products have a long cycle time; for example, to test the impact strength of parts (destructive testing). Individuals control charts include I charts and MR charts.

Minitab also offers I-MR and Z-MR combination charts for individuals. Use these to view both the process mean and the process variation at the same time.

Minitab also offers two other types of variables charts for more complex applications:

- Time-weighted control charts – Use historical data points to help you track small shifts in a process.
- Multivariate control charts – Show how correlated variables jointly affect a process or outcome.