Introducing the NEW STATGRAPHICS® Centurion XVII Powerful

Introducing the NEW
STATGRAPHICS® Centurion XVII
Powerful, intuitive software tools for data analysis, data
visualization, statistical modeling, and predictive analytics.
Statgraphics Version 17 is a comprehensive program for data visualization and predictive analytics.
It contains over 230 procedures covering everything from summary statistics to advanced statistical
models. Designed with the practitioner in mind, the program includes many features that make it
easier than ever to extract the vital information from your data.
Statgraphics Centurion XVII contains over 230 procedures covering:
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Analysis of Variance
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Basic Statistical Methods
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Categorical Data Analysis
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Data Mining
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Design of Experiments
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Exploratory Data Analysis
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Life Data Analysis and Reliability
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Measurement Systems Analysis
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Multivariate Methods
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Nonparametric Methods
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Probability Distributions
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Process Capability Analysis
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Regression Analysis
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Sample Size Determination
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Six Sigma and Lean
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Statistical Process Control
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Time Series Analysis and Forecasting
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Visualization
statgraphics.fr
DYNACENTRIX - 60, avenue Charles de Gaulle - 92200 Neuilly sur Seine - France
Tél : 01 72 92 05 58 - Fax : 01 72 92 05 99 - Email : [email protected]
Design of Experiments Wizard The DOE Wizard
guides users through the construction and analysis of
statistically designed experiments. Version 17 adds new
computer-generated designs which automatically create
runs to achieve A, D, G or I-optimality. The Response
Surface Explorer lets users dynamically change the level
of experimental factors to visualize the impact on the fitted
process model.
12-step process:
Step
Step
Step
Step
Step
Step
Step
Step
Step
Step
Step
Step
1: Define responses
2: Define experimental factors
3: Select design
4: Specify model
5: Select runs
6: Evaluate design
7: Save experiment
8: Analyze data
9: Optimize responses
10: Save results
11: Augment design
12: Extrapolate
Automatic Time Series Forecasting Given a series of
data collected over time, Statgraphics will automatically
generate forecasts for future observations by comparing
different types of models and selecting the best according
to a specified criterion (such as the Akaike Information
Criterion). The forecasts are plotted with prediction limits.
Tolerance Limits and Capability Indices The Statistical
Process Control section of Statgraphics calculates
statistical tolerance limits and process capability indices for
data from many probability distributions.
Fitted Largest Extreme Value Distribution
mode=203.355, scale=53.9342
24
95-99 Limits
UTL: 538.27
LTL: 94.36
Cpk = 0.85
20
frequency
HIGHLIGHTS
16
12
8
4
0
0
100
200
300
resistivity
400
500
600
Statlets® Version 17 contains 19 new Statlets, which are
graphical representations of data and statistical models
that may be dynamically manipulated with controls on the
Statlet toolbar. They let users visualize instantly the
effect of changing analysis options and dramatically reduce
the time required to develop an acceptable model.
Probability Distribution Fitting Statgraphics can fit up
to 45 different probability distributions to a set of data. The
data may be censored or uncensored. Critical values and
tail areas may be calculated from the fitted distributions,
and sets of random numbers may be generated.
Data Visualization Statgraphics contains many methods
for visualizing data. New in Version 17 are several dynamic
Statlets used to visualize changes in multivariate time
series. By manipulating the controls on the toolbar,
changes over time may be viewed dynamically.
FEATURES
SnapStats
SnapStats provide a quick way to produce a single page
of preformatted output. They are available for many
commonly used statistical analyses.
StatAdvisor
The StatAdvisor generates a paragraph or two interpreting
each table in your output. It explains the significance of
your results in simple terms, yet precisely enough that the
interpretations may be included in your reports.
Multivariate Methods Statgraphics contains many
methods for dealing with multivariate data, including
principal components analysis, PLS, MANOVA,
discriminant analysis and other advanced methods. Many
of these tools are useful for data mining and analysis of
big data. The program also contains many multivariate
visualization tools, such as scatterplot matrices, parallel
coordinate plots, multivariate glyphs, and corrgrams (new
in Version 17).
Pearson Product-Moment Correlations
0.94
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MPG City
0.94
1.00
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RPM
0.31
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1.00
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-0.33 -0.43 -0.55 -0.54 -0.44 -0.47
-0.62 -0.67
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1.00
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Fueltank
-0.79 -0.81 -0.33
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1.00
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Weight
-0.81 -0.84 -0.43
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Engine Size
-0.63 -0.71 -0.55
0.73
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1.00
0.87
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Width
-0.64 -0.72 -0.54
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Length
-0.54 -0.67 -0.44
0.55
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Wheelbase
-0.62 -0.67 -0.47
0.49
0.76
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Weight
Engine Size
Width
Length
Wheelbase
MPG Highway
Horsepower
RPM
1.00
MPG City
MPG Highway
Fueltank
1.0
Horsepower
-1.0
Demographic Maps Regional statistics are often
easiest to visualize when displayed on maps. Starting
with Version 17, maps may be generated for any area
defined by a BNA boundary file. For time series data,
a demographic map visualizer Statlet lets the user
interactively change the time period that is illustrated.
StatFolios
The StatFolio is the main Statgraphics document that
records the state of your session, including a link to
your data and all procedures and options that you have
selected. StatFolios may be saved and recalled at a later
date, or applied to multiple data sets.
StatGallery
The StatGallery lets you take graphs generated in different
procedures and arrange them side by side on a single
page. You may also overlay one graph on top of another.
StatLink
StatLink lets you link a StatFolio to one or more data
sources. When the data change, the contents of the
StatFolio is automatically updated.
StatLog
The StatLog, new to Version 17, automatically records the
operations you have performed and any output that you
choose to include. Together with the StatFolio audit trail,
it provides a permanent record of your analyses.
StatPublish
StatPublish lets you publish your tables and graphs as
HTML so that anyone with a web browser can quickly
view your results.
StatReporter
The StatReporter lets you create reports with Statgraphics
by copying and pasting tables and graphs generated
in the analysis windows. You may edit the output, add
additional comments, and save the results as an RTF file.
StatWizard
The StatWizard is a tool designed to help you select the
proper analyses for your data. You begin by selecting
the data to be analyzed. The StatWizard then suggests
analyses appropriate for that type of data.
statgraphics.fr
System Requirements
Windows XP, Vista, 7, 8 or later
At least 512MB of RAM
260MB or greater of available disk storage
CD-ROM drive or access to Internet
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•
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Editions
32-bit and 64-bit
English, French, German, Italian and Spanish
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Data Entry
Keyboard entry in datasheet
Copy and paste from Windows clipboard
Import of files from other programs (Excel and 25 other formats)
SQL queries using ODBC
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Report Generation
StatReporter and StatLog may be saved as RTF files
Copy and paste to Microsoft Word, Powerpoint, Excel and other programs
StatPublish saves results as HTML for access by web browsers
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Technical Support
DYNACENTRIX is dedicated to providing first-class technical support. Statgraphics.fr contains a
large number of instructional videos, how-to guides and recorded webinars. Our support specialists are also
available by e-mail or phone and are highly knowledgeable about both Statgraphics and statistical methods.
Training
DYNACENTRIX conduct both public and on-site seminars covering the use of Statgraphics Centurion
for statistical analysis. The seminars are appropriate for both new and advanced users.
Documentation
Statgraphics Centurion XVII comes with a 300-page User Guide which includes eight tutorials. 300 additional
PDF documents describe each statistical procedure in detail, with sample data files and mathematical formulas.
A context-sensitive help system can be used to search for specific topics or keywords. Statgraphics.fr
contains additional resources.
Validation
Before release of each new version, extensive tests are performed to ensure that the program operates properly.
For users needing to validate the statistical results for regulatory agencies, we will be happy to cooperate in
providing information about our software and development procedures.
How to Get Statgraphics
A trial copy of Statgraphics Centurion XVII can be downloaded from statgraphics.fr. The trial copy is fully
operational but expires after a limited number of days.
DYNACENTRIX
60, avenue Charles de Gaulle
92200 Neuilly sur Seine - France
Tél : 01 72 92 05 58
Fax : 01 72 92 05 99
[email protected]
statgraphics.fr
Statgraphics is a registered trademark of Statpoint Technologies, Inc. Statgraphics Centurion, StatAdvisor, StatFolio, StatLink, StatGallery, StatPublish,
StatReporter, SnapStats and StatWizard are trademarks of Statpoint Technologies, Inc.. Windows is a registered trademark of Microsoft Corporation.
© 2014 by Statpoint Technologies, Inc.
VERSION 17 ENHANCEMENTS
MAKING IT EASIER TO SEE TRENDS
AND VISUALIZE SUCCESS
Introducing the NEW
STATGRAPHICS® Centurion XVII
Version 17 contains 32 new statistical procedures and significant changes to 20 existing procedures.
The enhancements emphasize the increasing importance of data visualization, both for unlocking the
information that is often hidden in a large set of data and for understanding the meaning of statistical
methods applied to that data. Included in these enhancements is a set of dynamic Statlets®, which
let users visualize the effect of interactively changing analysis options and sampling intervals. The
visualization of multiple time series is especially important, where observing dynamic changes in graphs
over time can yield important insights. The most important enhancements are listed below.
DATA MANAGEMENT
1. Expanded data capacity – changes to the data editor and selected algorithms increase data limits.
2. New percentage data type – columns may now contain percentage signs.
3. Operators – operators have been added for trigonometric functions based on gradians.
4. Recent data file list – expanded to include Excel files and other file formats.
5. Select field – new functions added for identifying rows containing a specified string.
6. Storing data in StatFolio – data may now be saved in a StatFolio instead of a separate data file.
7. Value labels – allows specification of labels for discrete numeric columns.
GRAPHICS
1. Add object – adds additional objects to a graph such as a line, arrow, rectangle, ellipse or function.
2. Added text – may now specify reference position for text added to graph.
3. Brushing scatterplots – may now use a gradient fill to color points.
4. Change text font size – new button on analysis toolbar dynamically changes font size.
5. Dashed and dotted lines – may now increase width of dashed and dotted lines.
6. Override attribute – overrides color and style of a single object such as a line, point or bar.
7. Rotate X-axis tickmarks – new button on analysis toolbar rotates X-axis labels.
8. Video recording – new button added to analysis toolbar to simplify creation of videos.
9. Zoom and pan – new buttons on analysis toolbar zoom in and out on selected graph.
SYSTEM OPERATION
1. Audit trails and electronic signatures – tracks history of changes to a StatFolio.
2. Row numbers – new option for adding row numbers to many output tables.
3. StatFolio alerts – new alerts added for open-high-low-close plots.
4. StatFolio passwords – new user passwords added to StatFolios specifying custom privileges.
5. StatLog – session log file records all operations and selected analysis output.
6. Tabular options – overrides system defaults for a single text pane.
STATISTICAL PROCESS CONTROL
1. Cause-and-effect diagram – improved display of category labels.
2. G and T control charts – create control charts for the occurrence of rare events.
3. Laney P’ and U’ control charts – monitor overdispersed rates and proportions.
4. MIL-STD-105E, 414, and 1916 – generate sampling plans for attributes and variables.
5. P and U charts – new test added for overdispersion.
DESIGN OF EXPERIMENTS
1. Computer-generated designs – creates experimental designs based on A, D, G, or I-optimality.
2. DOE Wizard – number of responses increased from 16 to 32.
3. Linear constraints – may be specified for computer-generated designs.
4. 3-level fractional factorial designs – added to response surface design list.
STATLETS®
1. Bivariate density estimation – displays the joint distribution of two random variables.
2. Curve-fitting – allows interactive changes in powers of X and Y.
3. Demographic map brushing – colors regions red or blue based on a selected variable.
4. Demographic map visualizer – dynamically changes region colors for time series data.
5. Deviation dashboard – indicates the status of multiple variables as standard deviations from mean.
6. Exponential smoothing – allows interactive changes in smoothing parameters.
7. Interactive histogram – allows dynamic change in classes and density estimator window.
8. Kriging – maps the estimated mean and variance of geospatial data.
9. Multivariate visualizer – displays dynamic barchart, piechart, profile plot, strip plot or star plot.
10. One-dimensional visualizer – plots multiple time series as 1D dynamic bubble chart.
11. Power transformations – allows dynamic visualization of changes in power on Q-Q plot.
13. Probabilistic fractal – designed to illustrate the concepts of randomness and uncertainty.
14. Process capability analysis – displays effect on limits and indices of dynamically changing options.
15. Reliability demonstration test plan – demonstrates adequacy of failure time distribution.
16. Sample size determination – displays effect of dynamically changing inputs such as α and β.
17. Surface-fitting – allows interactive fitting and nonparametric LOWESS surface estimate.
18. Two-dimensional visualizer – plots multiple time series as 2D dynamic bubble chart.
19. Three-dimensional visualizer – plots multiple time series as 3D dynamic bubble chart.
OTHER NEW STATISTICAL PROCEDURES
1. Repeated measures ANOVA – analysis of one-way and two-way designs with sphericity corrections.
2. Item reliability analysis – estimates the reliability or consistency of a set of variables.
3. Ternary plot – creates a scatterplot of 3 variables which sum to a constant value.
CHANGES TO EXISTING PROCEDURES
1. Demographic map – now displays any area defined by BNA boundary file. New gradient fill.
2. Factor analysis and PCA – added KMO sampling adequacy measure and Bartlett’s test of sphericity.
3. Hypothesis tests – added tests for correlation coefficient and difference of two correlations.
4. Multiple sample comparison – added Games-Howell multiple sample comparison.
5. Multiple variable analysis – added corrgram, a colored matrix for visualizing correlations.
6. Nonlinear regression – increased number of unknown parameters from 12 to 36.
7. Normal probability plot – added percentiles, confidence limits and new method for fitting line.
For more detailed information on all Version 17 enhancements, visit www.statgraphics.fr.
DYNACENTRIX
60, avenue Charles de Gaulle
92200 Neuilly sur Seine - France
Tél : 01 72 92 05 58
Fax : 01 72 92 05 99
[email protected]
statgraphics.fr
CONTENTS
STATGRAPHICS.FR
designs
A A-optimal
Accelerated life tests
Acceptance control charts
Acceptance sampling
Adjusted R-squared
Adjusted residuals
Agglomeration distance plot
Agreement plot
Akaike’s information criterion
Algorithmic cusum chart
Alias matrix
All-possible regressions
Alpha plot
Alpha and beta risks
Analysis of covariance
Analysis of deviance
Analysis of means
Analysis of variance
Oneway & multifactor, GLM
Repeated measures designs
Variance components
Anderson-Darling test
Andrews plot
Annual subseries plot
AOQ curve
AOQL Plans
Appraiser variation
AQL
ARIMA control chart
ARIMA models
Arrhenius plot
ASN function
ATI curve
Autocorrelations
Automatic forecasting
Autoregressive models
Average run length
B Barcharts
Bartlett’s equal variance test
Bartlett’s sphericity test
Bernoulli distribution
Beta distribution
Bias analysis and correction
BIB designs
Bicubic splines
Binomial distribution
Biplot
Birnbaum-Saunders distribution
Bivariate capability analysis
Bonferroni intervals
Bivariate density
Bivariate normal distribution
Blocked designs
Bollinger bands
Bootstrap intervals
Box-and-whisker plots
Box-Behnken designs
Box-Cox transformations
Box-Pierce test
Brushing
Bubble chart
Buy-sell indicators
charts
C CCapability
analysis
Capability indices
CCpk, Cp, Cpk, Cpm
DPM, CM, CK, K
Non-normal indices
Sigma quality level
Within and between
Z-scores
Calibration models
Canonical correlations
Candlestick plot
Canonical variables plot
Capability ellipse
Casement plot
Cauchy distribution
Cause-and-effect diagram
Censored data analysis
Central composite designs
Chernoff faces
Chi-square decomposition
Chi-square distribution
Chi-squared test
City-block distance
Classification functions
Classification plot
Cluster analysis
Furthest and nearest neighbor
Ward’s method
k-means
Cochrane-Orcutt transformation
Coded scatterplot
Coefficient of variation
Collapse design
Comparison of regression slopes
Completely randomized designs
Component line chart
Communality
Compare proportions and rates
Comparison of correlation coefficients
Comparison of means and medians
Comparison of standard deviations
Component deviation plot
Component effects plot
Component extraction
Component loadings
Components of variance
Computer-generated experiments
Conditional gamma
Conditional sums of squares
Confounding pattern
Consumer and producer risk
Confidence bounds & intervals
Contingency coefficient
Contingency tables
Contour plot
Contrasts
Control chart design
Control ellipse
Control to standard
Cook’s distance
Correlations
Correspondence analysis
Correspondence map
Corrgram
Cost of quality trend analysis
Covariances
Covariates
Cox proportional hazards
Cox-Snell residuals
Cramer’s V
Cramer-Von Mises statistic
Cross-correlations
Crosstabulation
Cumulative distributions
Cumulative event plot
Critical values
Cronbach’s alpha
Cross-validation
Cube plot
Cubic spline
Cumulative failures plot
Cumulative hazard function
Cumulative Pareto chart
Cumulative score charts
Cumulative survival function
Curve fitting
Cuscore charts
CuSum charts
D D-efficiency
D-optimal designs
Data tapers
Death density function
Deleted residuals
Demographics map
Dendrograms
Density function
Density trace
Design of experiments
Analysis
Augmentation
Computer generated designs
Creation
Design resolution
Desirability functions
Multiple-variable optimization
Diagnostic plots
Discrete uniform distribution
Discriminant analysis
Discriminant functions plot
Dispersion dashboard
Dispersion index test
Distance graphs
Distribution fitting
Censored or uncensored data
Distribution-free tolerance limits
Dixon’s outlier test
Dot diagram
Draftsman’s plot
Draper-Lin designs
Duncan’s test
Dunnett’s procedure
Durbin-Watson statistic
tests
E EDF
Eigenvalues
Equimax rotation
Erlang distribution
Eta
Euclidian distance
Event plot
Event rate estimation
EWMA charts
EWMA decomposition
Expected mean squares
Exponential distribution
Exponential models
Exponential power distribution
Exponential smoothing
Brown’s, Holt’s, Winters' seasonal
Extrapolation
Extreme value distribution
Extreme value plot
Extreme vertices designs
F FF distribution
test
Factor analysis
Factor means plot
Factor plots
Factorability tests
Factorial designs
Failure rate statistics
False alarm rate
Financial plots
Fishbone diagram
Fisher’s exact test for 2x2 tables
Fisher’s LSD intervals
Fixed and random factors
Folded normal distribution
Folded Plackett-Burman designs
Forecasting
Fraction of design space plot
Fractal
Fractional factorial designs
Freedman-Diaconis rule
Frequency histogram and table
Frequency polygon
Frequency tabulation
Friedman test
chart
G GG-optimal
designs
Gage accuracy and linearity
Gage performance plot
Gage studies
Games-Howell method
Gamma distribution
Gauss-Newton method
General linear models
Generalized gamma distribution
Generalized logistic distribution
Generalized variance chart
Geometric distribution
Geometric mean
Geospatial data analysis
Glyphs
Goodness-of-fit tests
Gradient map
Graeco-Latin squares
Graphical ANOVA
Greenhouse-Geisser correction
Growth curve
Grubbs’ outlier test
chart
H H-K
Half-normal distribution
Half-normal plots
Hannan-Quinn criterion
Hanning
Hartley’s test
Hazard functions
Henderson’s moving average
Hierarchical designs
High-low-close plot
Histograms
Homogeneous groups
Homogeneous Poisson process
Hotelling-Lawley trace
House of quality
Huynh-Feldt correction
Hyper-Graeco-Latin squares
Hypergeometric distribution
Hypothesis tests
designs
I I-optimal
Icicle plots
Individuals control charts
Inertia
Inflation adjustment
Influential points
Inner and outer arrays
Integrated periodogram
Interaction analysis and plot
Interevent time distributions
Interpolation
Interquartile range
Interrater comparisons
Intersextile range
Inverse cumulative distributions
Inverse Gaussian distribution
Inverse prediction
Irregular fractions
Item reliability
J Jackknife
Jittering
measure
K Kaiser-Meyer-Olkin
Kaplan-Meier estimates
Kendall rank correlations
Kendall’s tau B and C
KMO
Kolmogorov-Smirnov tests
Kriging
Kruskal-Wallis test
Kuiper’s V
Kurtosis
tables
L Life
Lack-of-fit test
Lambda
Laney chart
Laplace centroid test
Laplace distribution
Largest extreme value distribution
Latin squares
Levene’s test
Least squares means
Leverage
Life data regression
Likelihood ratio test
Linear trend test
Linearity plot
Log probit model
Log survival functions
Log-cumulative hazard plot
Logarithmic models
Logistic distribution
Logistic regression
Logit transformation
Loglogistic distribution
Lognormal distribution
Lower and upper quartiles
LOWESS smoothing
LSD intervals
LTPD plans
regression
M MAD
Mahalanobis distance
Main effects plot
Mallows’ Cp
Mann-Whitney test
MAPE, MAE and MSE
Marquardt method
Martingale residuals
Matrix plot
Mauchley’s test
Maximum likelihood estimation
Maxwell distribution
Mean rank plots
Mean square PRESS
Mean time between failures (MTBF)
Mean, median & mode
Means and median plot
Measurement variation
Median chart
Median polish
Membership table
MIL-STD-105E, 1916 and 414
Mixed level fractions
Mixed models
Mixture designs
Mode
Monte Carlo simulation
Mood’s median test
Mosaic plot
Moving average charts
Moving range charts
Multi-vari charts
Multifactor ANOVA
Multifactor categorical designs
Multilevel factorial designs
Multiple comparisons
Multiple correspondence analysis
Multiple dot diagram
Multiple range tests
Multiple regression
Multiple response optimization
Multiple sample comparison
Multiple variable analysis
Multiple X-Y & X-Y-Z plots
Multiplicative models
Multivariate capability
Multivariate control charts
Multivariate EWMA chart
Multivariate T-squared chart
(no. of distinct categories)
N NDC
Negative binomial distribution
Negative binomial regression
Neural network classifier
Non-normal capability indices
Noncentral chi-square, t and F dists.
Nonhomogenous Poisson process
Nonlinear regression
Nonlinear smoothing
Nonparametric methods
Nonparametric tolerance limits
Normal distribution
Normal probability plot
Normal tolerance limits
Normalized control chart
Notched box-and-whisker plots
NP charts
curve
O OC
OC plans
Odds ratios
OHLC plots
One dimensional point processes
One variable analysis
Oneway ANOVA
Open-high-low-close plots
Operator and part plot
Optimization
Outlier identification
Overdispersion test
Overlaid contour plots
chart
P P’
P charts
P/T ratio
Paired sample comparison
Pairwise differences
Parallel coordinates plot
Parallel regression lines
Pareto charts
Pareto distribution
Partial autocorrelations
Partial correlations
Partial least squares (PLS)
Path of steepest ascent
Pearson correlations
Pearson curves
Pearson residuals
Percentiles
Periodogram
Perspective diagram
Phase 1 & Phase 2 analysis
Piechart
Pillai trace
Plackett-Burman designs
PLS
Point processes
Poisson distribution
Poisson regression
Polar coordinates plot
Polynomial regression
Power curve
Power function model
Power transformations
Prediction capability
Prediction limits
Prediction profile plot
Prediction R-squared
Prediction variance plot
PRESS residuals
Principal components
Probability distributions (45)
Probability plot
Probit analysis
Process mapping
Process Z
Profile plot
score statistic
Q QQuality
function deployment (QFD)
Quantile plot
Quantile-quantile plot
Quartiles
Quartimax rotation
charts
R RR-squared
R&R plot
Radar plot
Random censoring
Random number generators (45)
Random walk models
Randomized block designs
Randomness tests
Range chart
Rank correlations
Rank regression
Rayleigh distribution
Reciprocal models
Regression analysis
Relative inertia
Relative risk
Reliability analysis
Reliability test plans
Renewal processes
Repairable systems
Repeatability and reproducibility
Repeated measures
Residual autocorrelations
Residual distance graphs
Residual plots
Resistant regression
Resistant smoothing
Response surface designs
Response surface exploration
Reverse arrangement test
Ridge regression
Ridge trace
Risk analysis method
Robust parameter designs
Rootogram
Rotation of factors
Row and column profiles
Rowwise statistics
Roy’s greatest root
Run chart
Running medians
Runs tests
S SS chart
curves
S-squared chart
Sample size determination
Control charts
Correlation coefficients
One sample analysis
Oneway ANOVA
Rates and proportions
Screening designs
Two samples
Sampling distributions
Sbi
Scale cusum chart
Scatterplots
Scheffe intervals
Schwarz Bayesian criterion
Scott’s rule
Scree plot
Screening designs
Seasonal adjustment
Seasonal decomposition
Seasonal indices plot
Seasonal subseries plot
Sequential probability ratio tests
Session log and audit trail
Sextiles
Shapiro-Wilks’ test
Sigma plot
Sigma quality level
Sign test
Signal theory method
Signal-to-noise ratio
Signed rank test
Simplex plot
Simplex-centroid designs
Simplex-lattice designs
Simulation
Single factor categorical designs
Six sigma calculator
Skewness
Skychart
Smallest extreme value distribution
Smoothing
Somer’s D
Spearman rank correlations
Special cubic model
Specific variance
Spenser’s moving averages
Spherical coordinate plot
Sphericity correction
Sphericity tests
Spider plot
Splines
Standard deviation
Standard error bars
Standardized regression coefficients
Standardized residuals
Standardized skewness & kurtosis
Star plots
Statistical tolerance limits
Steepest descent method
Stem-and-leaf display
Stepwise regression
Strip plots
Student-Neuman-Keuls
Student’s t distribution
Studentized residuals
Sturges’ rule
Subset analysis
Sunray plots
Surface fitting
Surface plot
Survival functions
Suspended rootogram
Symmetry plot
chart
T Tt tests
T-squared chart
T-squared decomposition
Tabular cusum chart
Tabulation
Taguchi designs
Tail areas
Tapering
Ternary plot
Tests for normality
Tests for randomness
Three-level factorial designs
Time sequence plots
Time series analysis
Tolerance charts
Tolerance intervals and bounds
Toolwear charts
Trace plot
Trading bands
Trend models
Trend tests
Triangular distribution
Trimmed mean
Truncated sampling
Tukey’s 3-median method
Tukey’s HSD intervals
Tukey’s nonlinear smoothers
Two sample comparisons
Two-level factorial designs
Two-way table
Type I and II censoring
Type I and III sums of squares
chart
U U’
U charts
Uncertainty coefficient
Uniform distribution
Unusual residuals
User profiles
cusum chart
V V-mask
Variance
Variance check
Variance components analysis
Variance dispersion graph
Variance inflation factor
Variance map
Variance ratio test
Variation barchart
Varimax rotation
Variogram
Vertical time sequence plot
Video recording
Visualization
limits
W Warning
Watson’s U2 test
Weibayes method
Weibull analysis
Weibull distribution
Weibull plot
Weighted least squares
Wilcoxon test
Wilks’ lambda
Winsorized mean & sigma
X XX-Ycharts
& X-Y-Z Plots
X-bar charts
correction
Y Yates’
Yield plot
test
Z ZZero-based
acceptance
Z-scores