2
2D Bar/Column Plots
2D Box Plots
2D Box Plots - Box Whiskers
2D Box Plots - Boxes
2D Box Plots - Columns
2D Box Plots - Error Bars
2D Box Plots - Whiskers
2D Categorized Detrended Probability Plots
2D Categorized Half-Normal Probability Plots
2D Categorized Normal Probability Plots
2D Detrended Probability Plots
2D Histograms
2D Histograms - Hanging Bars
2D Histograms - Double-Y
2D Line Plots
2D Line Plots - Aggregrated
2D Line Plots - Double-Y
2D Line Plots - Multiple
2D Line Plots - Regular
2D Line Plots - XY Trace
2D Range Plots - Error Bars
2D Matrix Plots
2D Matrix Plots - Columns
2D Matrix Plots - Lines
2D Matrix Plots - Scatterplot
2D Normal Probability Plots
2D Probability-Probability Plots
2D Probability-Probability Plots - Categorized
2D Quantile-Quantile Plots
2D Quantile-Quantile Plots - Categorized
2D Scatterplot
2D Scatterplot - Categorized Ternary Graph
2D Scatterplot - Double-Y
2D Scatterplot - Frequency
2D Scatterplot - Multiple
2D Scatterplot - Regular
2D Scatterplot - Voronoi
2D Sequential/Stacked Plots
2D Sequential/Stacked Plots - Area
2D Sequential/Stacked Plots - Column
2D Sequential/Stacked Plots - Lines
2D Sequential/Stacked Plots - Mixed Line
2D Sequential/Stacked Plots - Mixed Step
2D Sequential/Stacked Plots - Step
2D Sequential/Stacked Plots - Step Area
2D Ternary Plots - Scatterplot


3
3D Bivariate Histogram
3D Box Plots
3D Box Plots - Border-style Ranges
3D Box Plots - Double Ribbon Ranges
3D Box Plots - Error Bars
3D Box Plots - Flying Blocks
3D Box Plots - Flying Boxes
3D Box Plots - Points
3D Categorized Plots - Contour Plot
3D Categorized Plots - Deviation Plot
3D Categorized Plots - Scatterplot
3D Categorized Plots - Space Plot
3D Categorized Plots - Spectral Plot
3D Categorized Plots - Surface Plot
3D Deviation Plots
3D Range Plot - Error Bars
3D Raw Data Plots - Contour/Discrete
3D Scatterplots
3D Scatterplots - Ternary Graph
3D Ternary Plots
3D Space Plots
3D Ternary Plots - Categorized Scatterplot
3D Ternary Plots - Categorized Space
3D Ternary Plots - Categorized Surface
3D Ternary Plots - Categorized Trace
3D Ternary Plots - Contour/Areas
3D Ternary Plots - Contour/Lines
3D Ternary Plots - Deviation
3D Ternary Plots - Space
3D Trace Plots


A
Aberration, Minimum
Abrupt Temporary Impact
Abrupt Permanent Impact
Accept-Support Testing
Accept Threshold
Activation Function (in Neural Networks)
Additive Season, Damped Trend
Additive Season, Exponential Trend
Additive Season, Linear Trend
Additive Season, No Trend
Adjusted means
AID
Algorithm
Alpha
Anderson-Darling Test
ANOVA
Append a network
Append Cases and/or Variables
Application Programming Interface (API)
Arrow
Assignable Causes and Actions
Asymmetrical Distribution
AT&T Runs Rules
Attribute (attribute variable)
Augmented Product Moment Matrix
Autoassociative Network
Automatic Network Designer


B
B Coefficients
Back Propagation
Banner Tables
Bar/Column Plots, 2D
Bar Dev Plot
Bar Left Y Plot
Bar Right Y Plot
Bar Top Plot
Bar X Plot
Bartlett Window
Batch algorithms in STATISTICA Neural Networks
Bayesian Networks
Best Network Retention
Beta Coefficients
Beta Distribution
Bimodal Distribution
Binomial Distribution
Bivariate Normal Distribution
Boundary Case
Box Plot/Medians (Block Stats Graphs)
Box Plot/Means (Block Stats Graphs)
Box Plots, 2D
Box Plots, 2D - Box Whiskers
Box Plots, 2D - Boxes
Box Plots, 2D - Whiskers
Box Plots, 3D
Box Plots, 3D - Border-style Ranges
Box Plots, 3D - Double Ribbon Ranges
Box Plots, 3D - Error Bars
Box Plots, 3D - Flying Blocks
Box Plots, 3D - Flying Boxes
Box Plots, 3D - Points
Box-Ljung Q Statistic
Breakdowns
Breaking Down (Categorizing)
Brown-Forsythe Test for Homogeneity of Variances
Brushing
Burt Table


C
Canonical Correlation
CART
Cartesian Coordinates
Casewise MD Deletion
Categorized Graphs
Categorized Plots, 2D - Detrended Probability Plots
Categorized Plots, 2D - Half-Normal Probability Plots
Categorized Plots, 2D - Normal Probability Plots
Categorized Plots, 2D - Probability-Probability Plots
Categorized Plots, 2D - Quantile-Quantile Plots
Categorized Plots, 3D - Contour Plot
Categorized Plots, 3D - Deviation Plot
Categorized Plots, 3D - Scatterplot
Categorized Plots, 3D - Space Plot
Categorized Plots, 3D - Spectral Plot
Categorized Plots, 3D - Surface Plot
Categorized 3D Scatterplot (Ternary graph)
Categorized Contour/Areas (Ternary graph)
Categorized Contour/Lines (Ternary graph)
Categorizing
Cauchy Distribution
Censoring (Censored Data)
Censoring, Left
Censoring, Multiple
Censoring, Right
Censoring, Single
Censoring, Type I
Censoring, Type II
CHAID
Characteristic Life
Chernoff Faces (Icon Plots)
Chi-square Distribution
Circumplex
City-Block Error Function in Neural Networks
City-block (Manhattan) distance
Classification
Classification Trees
Cluster Analysis
Cluster Diagram in Neural Networks
Codes
Coding Variable
Coefficient of Determination
Column Sequential/Stacked Plot
Columns (Box Plot)
Columns (Icon Plot)
Common Causes
Communality
Complex Numbers
Conditioning (Categorizing)
Confidence Interval
Confidence Interval for the Mean
Confidence limits
Confusion Matrix in Neural Networks
Conjugate Gradient Descent
Contour/Discrete Raw Data Plot
Contour Plot
Control, Quality
Cook's distance
Correlation
Correlation, Intraclass
Correlation (Pearson r)
Correspondence Analysis
Cpk, Cp, Cr
Cross Entropy in Neural Networks
Cross Verification in Neural Networks
Cross-Validation
Crossed Factors
Crosstabulations


D
Daniell (or Equal Weight) Window
Data Mining
Data Reduction
Data Rotation (in 3D space)
Data Warehousing
Deleted residual
Delta-Bar-Delta
Dependent vs. Independent Variables
Derivative-free Function Minimization Algorithms
Design, Experimental
Desirability Profiles
Detrended Probability Plots
Deviation
Deviation Plot (Ternary Graph)
Deviation Plots, 3D
DFFITS
Differencing (in Time Series)
Dimensionality Reduction
Discrepancy Function
Discriminant Function Analysis
DOE
Double-Y Histograms
Double-Y Line Plots
Double-Y Scatterplot
Drilling-down (Categorizing)


E
Ellipse, Prediction Area and Range
Endogenous Variable
Enterprise-Wide Software Systems
Entropy
Epoch in Neural Networks
Error Bars (2D Box Plots)
Error Bars (2D Range Plots)
Error Bars (3D Box Plots)
Error Bars (3D Range Plots)
Error Function in Neural Networks
Exogenous Variable
Experimental Design
Explained variance
Exponential Distribution
Exponential Family of Distributions
Exponential Function
Exponentially Weighted Moving Average Line
Extrapolation
Extreme Values (in Box Plots)
Extreme Value Distribution


F
F Distribution
FACT
Factor Analysis
Fast Analysis of Shared Multidimensional Information (FASMI)
Feedforward Networks
Fixed Effects (in ANOVA)
Free Parameter
Frequencies, Marginal
Frequency Scatterplot
Frequency Tables
Function Minimization Algorithms


G
Gamma Distribution
Gaussian Distribution
General ANOVA/MANOVA
Generalization in Neural Networks
Generalized Regression Neural Network (GRNN)
Genetic Algorithm
Genetic Algorithm Input Selection
Geometric Distribution
Geometric Mean
Gradient
Gradient Descent
Gradual Permanent Impact
GRNN (Generalized Regression Neural Network)
Group Control Charts
Grouping (Categorizing)
Grouping Variable
Groupware


H
Half-Normal Probability Plots
Half-Normal Probability Plots - Categorized
Hamming Window
Hanging Bars Histogram
Harmonic Mean
Hazard
Hazard Rate
Heuristic
Heywood Case
Hidden Layers in Neural Networks
Histograms, 2D
Histograms, 2D - Double-Y
Histograms, 2D - Hanging Bars
Histograms, 2D - Multiple
Histograms, 2D - Regular
Histograms, 3D Bivariate
Histograms, 3D - Box Plots
Histograms, 3D - Contour/Discrete
Histograms, 3D - Contour Plot
Histograms, 3D - Spikes
Histograms, 3D - Surface Plot
Hollander-Proschan Test
Hooke-Jeeves Pattern Moves
HTM
HTML
Hyperbolic tangent (tanh)
Hyperplane
Hypersphere


I
Icon Plots
Icon Plots - Chernoff Faces
Icon Plots - Columns
Icon Plots - Lines
Icon Plots - Pies
Icon Plots - Polygons
Icon Plots - Profiles
Icon Plots - Stars
Icon Plots - Sun Rays
Independent vs. Dependent Variables
Industrial Experimental Design
Inertia
Interactions
Interpolation
Interval Scale
Intraclass Correlation Coefficient
Invariance Under a Constant Scale Factor (ICSF)
Invariance Under Change of Scale (ICS)
Isotropic Deviation Assignment
Item and Reliability Analysis


J
JPEG
Jogging Weights
Johnson Curves
JPG


K
Kernel functions
K-Means algorithm
K-Nearest algorithm
Kohonen Networks
Kohonen Training
Kurtosis


L
Lambda Prime
Laplace Distribution
Latent Variable
Layered Compression
Learning Rate in Neural Networks
Least Squares (2D graphs)
Least Squares (3D graphs)
Least Squares Estimator
Left Censoring
Levenberg-Marquardt algorithm
Levene's Test for Homogeneity of Variances
Leverage values
Life Table
Life, Characteristic
Line Plots, 2D
Line Plots, 2D - Aggregrated
Line Plots, 2D (Case Profiles)
Line Plots, 2D - Double-Y
Line Plots, 2D - Multiple
Line Plots, 2D - Regular
Line Plots, 2D - XY Trace
Linear (2D graphs)
Linear (3D graphs)
Linear Activation function
Linear Modeling
Linear Units
Lines (Icon Plot)
Lines (Matrix Plot)
Lines Sequential/Stacked Plot
Local Minima
Logarithmic Function
Logistic Distribution
Logistic Function
Log-Linear Analysis
Log-normal Distribution
Lookahead in Neural Networks
Loss Function
Loss Matrix


M
Mahalanobis distance
Mann-Scheuer-Fertig Test
Mass
Manifest Variable
MANOVA
Marginal Frequencies
Matching Moments Method
Matrix Plots
Matrix Plots - Columns
Matrix Plots - Lines
Matrix Plots - Scatterplot
Maximum Likelihood Loss Function
Maximum Likelihood Method
Maximum Unconfounding
MD (Missing data)
Mean
Mean/S.D. algorithm in Neural Networks
Mean, Geometric
Mean, Harmonic
Mean Substitution of Missing Data
Means, Adjusted
Means, Unweighted
Median
Method of Matching Moments
Minimax
Minimum Aberration
Mining, Data
Missing values
Mixed Line Sequential/Stacked Plot
Mixed Step Sequential/Stacked Plot
Mode
Monte Carlo
MPatt Bar
Multidimensional Scaling
Multilayer Perceptrons
Multimodal Distribution
Multiple Censoring
Multiple Dichotomies
Multiple Histogram
Multiple Line Plots
Multiple Scatterplot
Multiple R
Multiple Regression
Multiple Response Variables
Multiple-response Tables
Multiplicative Season, Damped Trend
Multiplicative Season, Exponential Trend
Multiplicative Season, Linear Trend
Multiplicative Season, No Trend
Multi-way Tables


N
n Point Moving Average Line
N-in-One encoding
Negative Correlation
Negative Exponential (2D graphs)
Negative Exponential (3D graphs)
Neighborhood in Neural Networks
Nested Factors
Nested Sequence of Models
Neural Networks
Neuron
Noise Addition in Neural Networks
Nominal Scale
Nominal Variables
Nonlinear Estimation
Nonparametrics
Non-outlier range
Nonseasonal, Damped Trend
Nonseasonal, Exponential Trend
Nonseasonal, Linear Trend
Nonseasonal, No Trend
Normal Distribution
Normal Distribution, Bivariate
Normal Fit
Normal Probability Plots (Computation Note)
Normal Probability Plots
Normalization


O
Odds Ratio
On-Line Analytic Processing (OLAP)
One-of-N Encoding in Neural Networks.
One-Off in Neural Networks.
One-way Tables
Operating Characteristic Curves
Ordinal Scale
Outer Arrays
Outliers
Outliers (in Box Plots)
Overfitting
Overlearning in Neural Networks.


P
p-level (Statistical Significance)
Pairwise Deletion of Missing Data vs. Mean Substitution
Pairwise MD Deletion
Pareto Distribution
Partial Correlation
Parzen Window
Pearson Correlation
Pearson Curves
Penalty Functions
Percentiles
Pie Chart - Counts
Pie Chart - Multi-pattern Bar
Pie Chart - Values
Pies (Icon Plots)
PNN (Probabilistic Neural Networks)
Poisson Distribution
Polar Coordinates
Polygons (Icon Plots)
Polynomial
Positive Correlation
Post hoc Comparisons
Post Synaptic Potential (PSP) Function
Power Goal
Ppk, Pp, Pr
Process Capability Indices
Process Performance Indices
Prediction Interval Ellipse
Prediction Profiles
Predictive Mapping
Principal Components Analysis
Prior Probabilities
Probabilistic Neural Networks (PNN)
Probability Plots - Detrended
Probability Plots - Normal
Probability Plots - Half-Normal
Probability-Probability Plots
Probability-Probability Plots - Categorized
Process Analysis
Profiles, Desirability
Profiles, Prediction
Profiles (Icon Plots)
Pruning (in Classification Trees)
Pseudo-components
Pseudo-Inverse Algorithm
PSP (Post Synaptic Potential) Function


Q
Quadratic
Quality
Quality Control
Quantiles
Quantile-Quantile Plots
Quantile-Quantile Plots - Categorized
Quartile Range
Quartiles
Quasi-Newton Method
QUEST
Quick Propagation


R
r (Pearson Correlation Coefficient)
Radial Basis Functions
Random Effects (in Mixed Model ANOVA)
Range Ellipse
Range Plots - Boxes
Range Plots - Columns
Range Plots - Whiskers
Ratio Scale
Raw Data, 3D Scatterplot
Raw Data Plots, 3D - Contour/Discrete
Raw Data Plots, 3D - Spikes
Raw Data Plots, 3D - Surface Plot
Rayleigh Distribution
Regression
Regression, Multiple
Regular Histogram
Regular Line Plots
Regular Scatterplot
Regularization in Neural Networks
Reject Threshold
Relative Function Change Criterion
Reliability
Reliability and Item Analysis
Residual
Resolution
Response Surface
Right Censoring
RMS (Root Mean Squared) Error
Root Mean Square Standardized Effect (RMSSE)
Rosenbrock Pattern Search
Rotating Coordinates, Method of
Runs Tests (in Quality Control)


S
S.D. Ratio
Scalable Software Systems
Scaling
Scatterplot, 2D
Scatterplot, 2D - Categorized Ternary Graph
Scatterplot, 2D - Double-Y
Scatterplot, 2D - Frequency
Scatterplot, 2D - Multiple
Scatterplot, 2D - Regular
Scatterplot, 2D - Voronoi
Scatterplot, 3D
Scatterplot, 3D - Ternary Graph
Scree Plot, Scree Test
Sequential Contour Plot, 3D
Sequential/Stacked Plots, 2D
Sequential/Stacked Plots, 2D - Area
Sequential/Stacked Plots, 2D - Column
Sequential/Stacked Plots, 2D - Lines
Sequential/Stacked Plots, 2D - Mixed Line
Sequential/Stacked Plots, 2D - Mixed Step
Sequential/Stacked Plots, 2D - Step
Sequential/Stacked Plots, 2D - Step Area
Sequential Surface Plot, 3D
Shewhart Control Charts
Short Run Control Charts
Shuffle data in Neural Networks
Shuffle, Back Propagation in Neural Networks
Sigmoid function
Simplex algorithm
Single Censoring
Singular Value Decomposition
Skewness
Slicing (Categorizing)
Smoothing
SOFMs (Self-organizing feature maps; Kohonen Networks)
Softmax
Space Plots 3D
Special Causes
Spectral Plot
Spikes (3D graphs)
Spinning Data (in 3D space)
Spline (2D graphs)
Spline (3D graphs)
Split Selection (for Classification Trees)
Splitting (Categorizing)
Spurious Correlations
Square Root of the Signal to Noise Ratio (f)
Standard Deviation
Standard Error
Standard Error of the Proportion
Standard residual value
Standardized DFFITS
Standardized Effect (Es)
Stars (Icon Plots)
Stationary Series (in Time Series)
Statistical Power
Statistical Significance (p-level)
Steepest Descent Iterations
Steps
Stopping Conditions
Stopping Rule (in Classification Trees)
Stub and Banner Tables
Student's t Distribution
Studentized Deleted Residuals
Studentized Residuals
Sum-squared error function
Sun Rays (Icon Plots)
Supervised Learning in Neural Networks
Suppressor Variable
Surface Plot (from Raw Data)
Survival Analysis
Survivorship Function
Symmetric Matrix
Symmetrical Distribution


T
t Distribution (Student's)
Tables
Tapering
Ternary Plots, 2D - Scatterplot
Ternary Plots, 3D
Ternary Plots, 3D - Categorized Scatterplot
Ternary Plots, 3D - Categorized Space
Ternary Plots, 3D - Categorized Surface
Ternary Plots, 3D - Categorized Trace
Ternary Plots, 3D - Contour/Areas
Ternary Plots, 3D - Contour/Lines
Ternary Plots, 3D - Deviation
Ternary Plots, 3D - Space
THAID
Threshold
Time Series
Time-Dependent Covariates
Tolerance (in Multiple Regression)
Topological Map
Trace Plots, 3D
Trellis Graphs
Trimmed Means
Tukey Window
Two-State in Neural Networks
Type I Censoring
Type II Censoring
Type I Error Rate


U
Unconfounding, Maximum
Uniform Distribution
Unimodal Distribution
Unit Penalty
Unsupervised Learning in Neural Networks
Unweighted Means


V
Variance
Variance Components (in Mixed Model ANOVA)
Variance Inflation Factor (VIF)
Voronoi
Voronoi Scatterplot


W
Wald Statistic
Warehousing, Data
Weibull Distribution
Weigend Regularization
Weighted Least Squares
Win Frequencies in Neural Networks
Wire


X
X11 output: A 1.  Original Series
X11 output: A 2.  Prior Monthly Adjustment Factors
X11 output: A 3.  Original Series Adjusted by Prior Monthly Adjustment Factors
X11 output: A 4.  Prior Trading Day Adjustment Factors
X11 output: B 1.  Prior Adjusted Series or Original Series
X11 output: B 2.  Trend-cycle
X11 output: B 3.  Unmodified S-I Differences or Ratios
X11 output: B 4.  Replacement Values for Extreme S-I Differences (Ratios)
X11 output: B 5.  Seasonal Factors
X11 output: B 6.  Seasonally Adjusted Series
X11 output: B 7.  Trend-cycle
X11 output: B 8.  Unmodified S-I Differences (Ratios)
X11 output: B 9.  Replacement Values for Extreme S-I Differences (Ratios)
X11 output: B 10.  Seasonal Factors
X11 output: B 11.  Seasonally Adjusted Series
X11 output: B 13.  Irregular Series
X11 output: B 14.  Extreme Irregular Values Excluded from Trading-day Regression
X11 output: B 15.  Preliminary Trading-day Regression
X11 output: B 16.  Trading-day Adjustment Factors Derived from Regression Coefficients
X11 output: B 17.  Preliminary Weights for Irregular Component
X11 output: B 18.  Trading-day Factors Derived from Combined Daily Weights
X11 output: B 19.  Original Series Adjusted for Trading-day and Prior Variation
X11 output: C 1.  Original Series Modified by Preliminary Weights and Adjusted for Trading-day and Prior Variation
X11 output: C 2.  Trend-cycle
X11 output: C 4.  Modified S-I Differences (Ratios)
X11 output: C 5.  Seasonal Factors
X11 output: C 6.  Seasonally Adjusted Series
X11 output: C 7.  Trend-cycle
X11 output: C 9.  Modified S-I Differences (Ratios)
X11 output: C 10.  Seasonal Factors
X11 output: C 11.  Seasonally Adjusted Series
X11 output: C 13.  Irregular Series
X11 output: C 14.  Extreme Irregular Values Excluded from Trading-day Regression
X11 output: C 15.  Final Trading-day Regression
X11 output: C 16.  Final Trading-day Adjustment Factors Derived from Regression X11 output: Coefficients
X11 output: C 17.  Final Weights for Irregular Component
X11 output: C 18.  Final Trading-day Factors Derived From Combined Daily Weights
X11 output: C 19.  Original Series Adjusted for Trading-day and Prior Variation
X11 output: D 1.  Original Series Modified by Final Weights and Adjusted for Trading-day and Prior Variation
X11 output: D 2.  Trend-cycle
X11 output: D 4.  Modified S-I Differences (Ratios)
X11 output: D 5.  Seasonal Factors
X11 output: D 6.  Seasonally Adjusted Series
X11 output: D 7.  Trend-cycle
X11 output: D 8.  Final Unmodified S-I Differences (Ratios)
X11 output: D 9.  Final Replacement Values for Extreme S-I Differences (Ratios)
X11 output: D 10.  Final Seasonal Factors
X11 output: D 11.  Final Seasonally Adjusted Series
X11 output: D 12.  Final Trend-cycle
X11 output: D 13.  Final Irregular
X11 output: E 1.  Modified Original Series
X11 output: E 2.  Modified Seasonally Adjusted Series
X11 output: E 3.  Modified Irregular Series
X11 output: E 4.  Differences (Ratios) of Annual Totals
X11 output: E 5.  Differences (Percent Changes) in Original Series
X11 output: E 6.  Differences (Percent Changes) in Final Seasonally Adjusted Series
X11 output: F 1.  MCD (QCD) Moving Average
X11 output: F 2.  Summary Measures
X11 output: G 1.  Chart
X11 output: G 2.  Chart
X11 output: G 3.  Chart
X11 output: G 4.  Chart


Y
Yates Corrected Chi-square
Year 2000 Compatibility