STATISTICA Quality Control Charts
Features list
Standard charts
The program offers flexible implementations of Pareto charts, X-bar charts, R charts, S charts, S-squared (variance) charts, C charts, Np charts (binomial counts), P charts (binomial proportions), U charts, CuSum (cumulative sum) charts, moving range charts, runs charts (for individual observations), regression control charts, MA charts (moving average), and EWMA charts (exponentially-weighted moving average). These charts may be based on user-specified values or on parameters (e.g., means, ranges, proportions, etc.) computed from the data. Most of the variable control charts can be constructed from single observations (e.g., moving range chart) as well as from samples of multiple observations. Control limits can be specified in terms of multiples of sigma (e.g., 3 * sigma), in terms of normal or non-normal (Johnson-curves) probabilities (e.g., p=.01, .99), or as constant values. For unequal sample sizes, control charts can be computed with variable control limits or based on standardised values. For most charts, multiple sets of specifications can be used in the same chart (e.g., control limits for all new samples can be computed based on a subset of previous samples, etc.). As with all STATISTICA graphs, QC charts in STATISTICA Quality Control Charts are highly customisable; you can add titles, comments, draw lines or mark regions dynamically anchored to specific scale values, or label the samples with dates, ID codes, etc.
Chart options and statistics
A wide variety of additional quality control statistics are included. The user can compute the process capability and performance indices (e.g., normal distribution Cpk, Ppk, etc., non-normal distribution Cpk, Ppk, etc.), include histograms of the respective quality characteristics, or automatically perform any or all of seven different runs tests (runs rules). The standard variable control charts can be produced as compound multigraphic displays; for example, the X-bar and the R (or S, or S-squared) chart will be displayed together with optional corresponding histograms for the respective means, ranges, proportions, etc. also shown in the same chart. Outliers (samples outside the control limits) or sections of data identified via runs tests are automatically highlighted (marked) in the plots. The user can also add to the plot warning lines, moving average or exponentially-weighted moving average lines, or lines indicating specification ranges.