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StatControlCharts Namespace

Control charts.

Introduces several control charts. Control charts are used to routinely monitor quality. Depending on the number of process characteristics to be monitored, there are two basic types of control charts. The first, referred to as a univariate control chart, is a graphical display (chart) of one quality characteristic. The second, referred to as a multivariate control chart, is a graphical display of a statistic that summarizes or represents more than one quality characteristic. 

 

If a single quality characteristic has been measured or computed from a sample, the control chart shows the value of the quality characteristic versus the sample number or versus time. In general, the chart contains a center line that represents the mean value for the in-control process. Two other horizontal lines, called the upper control limit (UCL) and the lower control limit (LCL), are also shown on the chart. These control limits are chosen so that almost all of the data points will fall within these limits as long as the process remains in-control. 

Check the following linkto learn more about probability plots.

Name 
Description 
The following table lists functions in this documentation. 
 
Name 
Description 
 
Calculates the Exponential Weighted Moving Average (EWMA) control chart. 
 
Constructs EWMA Control Chart. 
 
Process Capability indexes p, Cp and Cpk. 
 
Constructs C-Chart. 
 
CUMSum chart. 
 
Moving range chart. 
 
Constructs nP-Chart. 
 
In this case each sample can have different size. You must store sizes in SampleSize vector. 
 
P-Chart. 
 
In this case each sample can have different size. You must store sizes in SampleSize vector. 
 
R-Chart. 
 
S-Chart. 
 
U-Chart. 
 
In this case each sample can have different size. You must store sizes in SampleSize vector. 
 
Compares values agains Westgard rules. 
 
X-Chart ("XBar Chart"). 
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