Overview
The MACHART statement creates a uniformly weighted moving average
control chart (commonly referred to as a moving average control chart),
which is used to decide whether
a process is in a state of statistical control and to detect shifts in
the process average.
You can use options in the MACHART statement to
- specify the span of the moving averages (the
number of terms in the moving average)
- compute control limits from the data based on a multiple of
the standard error of the plotted moving averages or
as probability limits
- tabulate the moving averages,
subgroup sample
sizes, subgroup means, subgroup standard deviations,
control limits, and other information
- save control limit parameters in an output data set
- save the moving averages,
subgroup sample sizes, subgroup means, and subgroup standard
deviations in an output data set
- read control limit parameters from an input data set
- specify one of several methods for estimating the process
standard deviation
- specify a known (standard) process mean and standard deviation
for computing control limits
- display a secondary chart that plots a time trend that has
been removed from the data
- add block legends and symbol markers to reveal
stratification in process data
- superimpose stars at points to represent related
multivariate factors
- clip extreme points to make the chart more readable
- display vertical and horizontal reference lines
- control axis values and labels
- control layout and appearance of the chart
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
