Dictionary of statistics
Statistical
Process Control
Statistical Process Control (SPC)
techniques can be used to highlight areas that would benefit from further
investigation. These techniques enable the user to identify variation within
the process being examined. Understanding this variation is the first step
towards quality improvement. There are many different SPC techniques that can
be applied to data. The simplest SPC techniques to implement are the control
charts.
The purpose of these techniques is to identify when the process is producing
unusual behaviour or figures.
The two types of variation that are
most commonly used in the NHS are ‘common cause’ and ‘special cause’ variation.
Common Cause
All processes have random
variation - known as ‘common cause variation’. A process is said to be ‘in
control’ if it exhibits only common cause variation i.e. the process is
completely stable and predictable.
Special Cause
Unexpected events/unplanned
situations can result in ‘special cause variation’. A process is said to be
‘out of control’ if it exhibits special cause variation i.e. the process is
unstable.
SPC charts are a good way to differentiate
these types of variation.
Boxplot
A box plot is a way of summarising
a measured set of data. It is a type of graph which is used to show the shape
of the distribution, its central value, and variability. The picture produced
consists of a maximum and minimum value, lower and upper quartiles,
and the median.
The
median divides the data into two equal sets. The lower quartile is the value of
the middle of the first set, where 25% of the values are smaller than lower
quartile and 75% are larger. The upper quartile is the value of the middle of
the second set, where 75% of the values are smaller than the upper quartile and
25% are larger.
Box plots with a larger
difference between the maximum and minimum value have a larger range. A longer
box shows a greater spread between the upper and lower quartile values, this shows
that the process values are typically further from the median.
A box plot is particularly
helpful for indicating whether a distribution is skewed and whether there are
any unusual observations (outliers)
in the data set.
Box plots are also very useful
when large numbers of observations are involved and when two or more data sets
are being compared.