The following guides, authored by
Dr. Neil W. Polhemus,
are designed to help you get the most out of STATGRAPHICS
Centurion. They deal with problems beyond what you often see
in textbooks, but which occur all too often in practice.
(Note: new guides will be added as they are completed, so check back
often.)

Describes the construction of a
statistical model to aid in setting the shelf life
of a product. Includes fitting of nonlinear and
polynomial regression models.

Describes the construction of an ARIMA control chart
to deal with data in which adjacent samples are not
independent. Includes identification of the proper
ARIMA model using Automatic Forecasting.

Describes a method to deal with correlated predictor
variables when constructing a multiple regression
model. Includes the use of Variance Inflation
Factors and Ridge Regression.

Describes methods for forecasting data that follows
a seasonal pattern. Includes seasonal decomposition,
seasonal exponential smoothing, and seasonal ARIMA
models.

Describes the proper application
of SPC methods to multiple correlated variables.
Includes use of the Multivariate Capability Analysis
and Multivariate Control Charts procedures.

Describes a suggested approach to optimization using
the DOE procedures. Includes the construction of an
initial design, augmenting the design, following the
path of steepest ascent, and optimizing multiple
responses.

Presents two examples of
split-plot designs with instructions on how to
analyze them. Includes a split-plot design with two
categorical factors and a fractional factorial
design run with restricted randomization on some
factors.