Quality Control Charts for Variable Lists - Variables Tab

Select the Variables tab of the Quality Control Charts for Variable Lists Startup Panel to access the options described here.

SixGraph with X-bar & R chart

Select SixGraph with X-bar & R chart and click the OK button on the Startup Panel to begin this analysis, which produces SixGraph compound graphs and X-bar charts (for means) and an R (range) charts for the variability of the processes (you can also double click SixGraph with X-bar & R chart to start the analysis).

SixGraph with X-bar & S chart

Select SixGraph with X-bar & S chart and click the OK button to begin this analysis, which produces SixGraph compound graphs and X-bar charts (for means) and an S (standard deviation) charts for the variability of the processes.

SixGraph with X & MR chart

Select SixGraph with X-bar & MR chart and click the OK button to begin this analysis, which produces SixGraph compound graphs and X (for individuals) charts and MR (moving range) charts for the variability of the processes.

X-bar & R chart for variables

Select X-bar & R chart for variables and click the OK button to begin this analysis, which produces X-bar charts (for means) and an R (range) charts for the variability of the processes.

X-bar & S chart for variables

Select X-bar & S chart for variables and click the OK button to begin this analysis, which produces an X-bar chart (for means) and an S (standard deviation) chart for the variability of the process.

MA X-bar & R chart for variables

Select MA X-bar and R chart for variables and click the OK button to begin this analysis, which produces MA (moving average) charts. In these charts, a moving average of means (or individual observations) across a specified number of successive samples is plotted, and control lines are established around that moving average line. This is useful for detecting small permanent shifts (trends) in the process average. Note that these charts can be constructed for individual observations (N=1), in which case sigma will be estimated from moving ranges.

MA X-bar & S chart for variables

Select MA X-bar and S chart for variables and click the OK button to begin this analysis, which produces MA (moving average) charts. In these charts, moving averages of means (or individual observations) across a specified number of successive samples are plotted, and control lines are established around the moving average lines. This is useful for detecting small permanent shifts (trends) in process averages.

EWMA X-bar & R chart for variables

Select EWMA X-bar and R chart for variables and click the OK button to begin this analysis, which produces EWMA (exponentially weighted moving average) charts. Instead of plotting the simple averages of a particular numbers of successive sample means, these means are weighted so that historically "older" means are assigned increasingly smaller weights. This is useful for detecting small permanent shifts (trends) in the process averages. Note that these charts can be constructed for individual observations (N=1), in which case sigma will be estimated from moving ranges.

EWMA X-bar & S chart for variables

Select EWMA X-bar and S chart for variables and click the OK button to begin this analysis, which produces EWMA (exponentially weighed moving average) charts. Instead of plotting the simple averages of particular numbers of successive sample means, these means are weighted so that historically "older" means are assigned increasingly smaller weights. This is useful for detecting small permanent shifts (trends) in the process averages.

Individuals & moving range

Select Individuals & moving range and click the OK button to begin this analysis, which produces charts for individual observations and moving ranges. In these plots individual observations (sample size of 1) are plotted and you can use so-called moving ranges (of adjacent observations) in order to estimate a process sigma and establish control limits. Note that MA and EWMA charts can also be constructed for individual observations, in which case sigma will also be estimated from moving ranges.

CuSum chart for individuals

Select CuSum chart for individuals and click the OK button to begin this analysis, which produces CuSum (cumulative sum) charts for individual observations. These charts are useful for controlling trends or minor mean shifts in a variables related to quality. Note that STATISTICA computes the recommended tabular or algorithmic CuSum charts, and not the "old-style" V-mask control limits that were commonly in use when these charts were (literally) made by hand. See Montgomery (1996, Chapter 7) for details and recommendations.

Pareto chart analysis

Select Pareto chart analysis and click the OK button to begin this analysis, which produces Pareto charts. You can plot histograms by category, where the bars in the histogram are sorted in descending order. Such plots allow for the easy identification of the primary sources (categories) of quality problems.

See also, Common Types of Charts, Control Charts for Variables vs. Charts for Attributes, and the Quality Control Charts Index.