Stat-Ease, Inc. is
proud to announce Design-Ease, Version 7.1. This
easy-to-use software sets up and analyzes powerful general and two-level
factorials that identify the critical factors for improvement of products and
processes. Use it to make breakthrough discoveries that save you time and money.
(Download the free 45-day trial at http://www.statease.com/soft_ftp.html.)

Those of you who¡¯ve used previous versions of
Design-Ease software will be impressed with the many improvements in Version
7.1. See changes since version 7.0 in the "What's
New" section below.

What's New in Version 7.1

Upfront power calculation for
factorial designs:This mainstreams in
the design-builder a ¡®heads-up¡¯ on the percent probability of seeing the desired
difference in each response — the signal — based on the underlying variability —
the noise.

¡°Min-Run Res V¡± designs are now available for 6
to 50 factors: Resolve two-factor
interactions (2FI's) in the least runs possible while maintaining a balance in
low versus high levels.

Bookmarks for reports with a toolbox to facilitate selection:This will save you a lot of time scrolling through
long statistical outputs such as the design evaluation and analysis of
variance.

Display grid lines on 3D-graph
back-planes:This feature provides a
better perspective on the varying height of a response
surface.

Save graphs to files in enhanced Windows metafile
(EMF), PNG, TIFF, GIF, BNP, JPEG, and encapsulated Postscript (EPS)
formats:Many publications do their
artwork in one of these file types .

Fraction of design space (FDS) graph for design evaluation: This
enhancement, suggested to us by DOE guru Douglas Montgomery, provides very
helpful information on scaled prediction variance (SPV) for comparing
alternative test matrices — simple enough that even non-statisticians can see
differences at a glance and versatile enough for any type of experiment —
mixture, process or combined.

Design layout can now be modified via a right-click
list with added columns for point type and other alternative
attributes:Make your "recipe" sheet
more informative.

¡°Design model¡± choice added for statistical
analysis:This is handy for data from
experiments based on a computer-generated D-optimal design.

More flexibility in handling various file types when opening files: Very
helpful default that automatically recognizes any data in the Design-Ease (.de*)
or Design-Expert (.dx*) format – including ones produced from older
versions.

Keystroke option (Ctrl+/-) to move through alternate solutions from
numerical optimization: This saves mousing around.

Import and export text files to get responses: Something do-able by
anybody

Write transfer functions in format (.vta) readable by VarTran® software
(Taylor Enterprises): This sets the stage for statistical tolerancing and
sensitivity analysis leading to more robust
designs.

Other great features you will find in
Design-Ease 7.1 software include: A Variety
of Design Creation Tools to Meet All Your Experimental Needs

¡°Min-Run Res IV¡± (two-level factorial) designs for 5 to 50 factors: Screen main effects with maximum efficiency in terms of
experimental runs.

Two-level full and fractional factorials for up to 512 runs and 21 factors,
along with minimum-aberration blocking choices:
Build large designs.

New ¡°Color By¡± option: Color-code points on
graphs according to the level of another factor—a great way to incorporate
another piece of information into a graph.

General (multilevel) factorial designs (up to 32,766 runs) using factors
with mixed levels.

High-resolution irregular fractions, such as 4 factors in 12 runs.

Placket-Burman designs for 11, 19, 23, 27 or 31 factors in up to 64 runs
respectively.

Taguchi orthogonal arrays.

Ability to graph any two columns of data on the XY graph (this is a great
way to view a blocked effect).

Easy-to-use automatic or manual model reduction.

Ability to easily analyze designs with botched or missing data.

Design-builder updates resolution of two-level fractional factorials when
the number of blocks is changed: Immediately see
how segmenting a design might reduce its ability to resolve
effects.

Block names are now entered during the design build: Identify how you will break up your experiment, for
example by specific shift, material lot or the like.

¡°Min-Run Res IV plus two¡± option: Ask for two
extra runs to make your experiment more robust to missing data.

User-defined base factors for design generators: You have more flexibility to customize fractional
factorial designs.

Expanded D-optimal capabilities—impose balance penalty, force categoric
balance: This feature helps users equalize the
number of treatments.

Coordinate Exchange capability for D-optimal designs: Avoid the arbitrary nature of designs constructed from
candidate point sets.

In General or Factorial D-optimal designs, categorical factors can be
specified as either nominal or ordinal (orthogonal polynomial contrasts): This affects the layout of analysis of variance
(ANOVA).

Enjoy Incredible
Flexibility with Design Modification & Augmentation Tools

Add blocks D-optimally

¡°Semifold¡±: In only half the runs needed by a
normal foldover, augment Res IV designs to resolve specified 2FI's aliased in
the original block of runs.

Add center points, blocks and replicates without rebuilding the design:
This is a real time-saver.

Ignore or highlight a row of data or a single response while preserving the
numbers.

Build Confidence with
Statistical Analysis of Data

From Alias List, Pareto Chart or Effects Plots views, right-click on effects
to show aliases: Never lose sight of what really
is being measured in fractional-factorial designs.

Select alternative aliased effects: Choose
what you think makes most sense based on your subject-matter
knowledge.

Backward stepwise regression is now applicable to factorial designs: This is useful for quickly analyzing general
(categorical) factorials.

Means and standard deviations for all experimental inputs (factors) and
outputs (responses) are added to the Design Summary screen: This provides a handy assessment of your
system.

The user can define their preference for sums of squares calculations for
both numeric and categoric factors to be sequential, classical, or partial: These distinctions are important for statisticians who
want to do ANOVA in specific ways.

Select terms for model, error, or to be ignored (allows analysis of
split-plot and nested designs).

Select optional annotated views for assistance interpreting the
ANOVA.

If your model is aliased, a warning will pop up prior to viewing the ANOVA
for two-level fractional factorials, allowing you to make substitutions for
aliased effects.

Inspect F-test values on individual model terms and confidence intervals on
coefficients.

Take advantage of user preferences, ex: make a
global change in the significance threshold (0.05 by default vs. 0.01 and
0.1).

Spot Problematic or
Influential Data with Diagnostics Tools

Row(s) in the design layout are highlighted when point(s)
are selected on the diagnostics: The highlighting
feature makes identification of problematic data much easier.

Box-Cox transformation parameters added to the diagnostics
report: Includes stats that may not appear on the plot.

DFFITS: Spot influential runs
via this deletion diagnostic that measures difference in fits when any given
response is removed from the dataset.

DFBETAS: See from this
deletion diagnostic how model terms change due to an influential
run.

Simplify Interpretation
with Terrific Graphics

Full-color contour and 3D surface plots:Graduated or banded colorization adds life to reports
and presentations.

3D surface plots for categorical factors: See
colored bars towering above others where effects are greatest.

Pareto chart of t-values of effects: Quickly
see the vital few effects relative to the trivial many from two-level factorial
experiments.

Magnification feature: An incredible tool for
expanding a mixture graph that is originally a small sliver and difficult to
interpret.

Points on 3D graphs: See "lollipops"
protruding from surfaces where actual responses were collected.

Crosshairs window: Predict your response at
any place in the response surface plot.

Grid lines on contour plots: See more readily
what the coordinates are at any given point.

Select the details printed on flags planted on contour
plots.

Color-codes for positive versus negative effects: Assess plus or minus impacts on half-normal and Pareto
plots.

Smart tic marks: Get
more-reasonably rounded settings straight off.

A quick summary of the design type as well as factor, response and model
information is available by clicking on the design status node.

Discover significant effects at a glance with half-normal or normal
probability plots, made easier by including points representing estimates of
pure error (if available from your design).

See the Box-Cox plot for advice on the best response transformation.

View a complete array of diagnostic graphs to check statistical assumptions
and detect possible outliers (bonus feature:
predicted vs. actual graphs with a rotatable best-fit line).

See the effects plot in the original scale after transforming the
response.

Observe variation in predictions by viewing the least significant difference
(LSD) bars on the model graphs.

Poorly predicted regions on contour maps are shaded to give you confidence
in your predictions.

Slice your contour plots using a simple slide bar: See actual design points
when they're on a slice!

Drag 2-D contours using your mouse.

Rotate 3-D graphics and see projected 2-D contours.

Set flags to reveal the predicted response at any location.

Edit colors, text and more to produce professional reports.

See all effects on one graph with trace and perturbation plots.

Plot the standard error of your design on any graph type (contour, 3D,
etc.).

Locate Your Sweet Spot with Multiple Response
Optimization

Maximize, minimize or target specific levels for both responses and
factors.

Set weight and importance levels to prioritize responses for
desirability.

Choose 2-D contour, 3-D surface, histogram or ramp desirability
graphs.

Include categorical factors.

Set factors at constant levels.

Add equation-only responses, such as cost, to the optimization
process.

Look at the overlay plot to view constraints on your process or
formulation.

Predict responses at any set of conditions (including confidence
levels).

Discover optimal process conditions or
formulations.

Achieve Six-Sigma Goals

Explore propagation of error (POE) for mixtures, combined designs and
transformed responses, as well as RSM.

For purposes of POE, enter your own response standard deviation or set it at
zero.

Save Time with
Design-Ease's Intuitive User Interface

Right-click on any response cell and ¡°ignore¡± it: This feature allows you to ignore a response data point
without having to ignore the entire row.

On plots of effects simply draw a box around the ones you want selected for
your model: This is much easier than clicking each
one with your mouse.

Set row status to normal, ignore or highlight: This allows users control over their design
matrix.

Sort by row status — normal, ignored or highlighted: Most real-life
experiments do not go as planned so it¡¯s good to easily assess the
damage.

Numerical optimization solutions are now carried over to graphical
optimization and point prediction: Explore the
results of the numerical optimization on other screens.

Cut and paste graphics to your word processor or presentation, or numbers to
and from a spreadsheet.

Easily maneuver through the program: down trees, through wizards, and across
progressive toolbars.

Tab flow through all fields on the screen: Quicker for data entry than
having to click your mouse in a new location.

Quickly select the next step with incredibly easy-to-use push
buttons.

Open reports and graphs for automatic updating.

View numerical outputs spreadsheet style.

Export any spreadsheet view as ASCII text, for example, design layouts or
ANOVA reports.

View several graphs simultaneously using the handy pop-out option.

32-bit architecture provides maximum performance on Windows 2000, XP and
beyond.

Access graphic and spreadsheet options instantly with a simple right
click.

Choose significant terms to plot from the pull-down list on the Factors
Tool.

Handy Tools for Design Evaluation

Annotation option on reports: This will be a
boon to those who may be unfamiliar with all the esoteric statistics needed for
design evaluation.

Customizable design evaluation content and power levels: Use the OPTIONS button to select which statistics to
display, specific power levels to report, and whether to display the standard
error or variance on the graph (with the option to scale by N—the number of runs
in the design).

Specify model terms to ignore (during evaluation) so they don¡¯t display in
the alias list: For example, don¡¯t bother showing
interactions of four or more factors.

Evaluation can be done on either a design or a particular response: Shows the effect when data is missing from a specific
response, but not all responses.

Find Answers to your Questions in Help

¡°Screen tips¡±: Press the new tips button for
enlightenment on the current screen—this is especially helpful for novice
users.

Tutorial movies: See Flash demo¡¯s of features
via Screen Tips—a very effective way to show how to navigate through the
software.

Internet links: These are helpful connections
to further information.

Better guidance helps you choose the best model.

A bonus help section provides "quick start"
advice.

Import/Export Tools Increase Flexibility

XML (eXtensible Markup Language) capability: Export design files or reports in a viewable format that
can be manipulated for further processing. (The XML tool also allows import of
designs created externally.)

Extras!

Free technical support

Limited free statistical support

Helpful tutorials to illustrate the most powerful features

30-day money-back guarantee

Try out Design-Ease, Version 7.1 software's
many great features with our fully-functional trial.