Stat Soft: Statistics Glossary

believable correlation, correlation diagrams, counting procedure, curve-fitting, data collection method, data interpretation, definitions, discrete probability distribution, display distortion, equal likelihood, equivalent representation, experimental outcome, goodness-of-fit, independent trials, law of probability, linear transformation, measure of goodness, measurement data, measurement error, median-fit line, misleading presentation, misrepresentation, monte carlo simulation, normal curve, point of vew, quartile deviation, question formulation, set relationships, statistic probability, statistical design, statistical interpretation, statistics glossary, statistics terms, statistics vocabulary, summary statistics, t-test (for independent and dependent samples), true correlation, type of data, aid, anova, at&t runs rules, aberration, minimum, abrupt permanent impact, abrupt temporary impact, accept threshold, accept-support testing, activation function (in neural networks), additive season, damped trend, additive season, exponential trend, additive season, linear trend, additive season, no trend, adjusted means, algorithm, alpha, anderson-darling test, append cases and/or variables, append a network, application programming interface (api), arrow, assignable causes and actions, asymmetrical distribution, attribute (attribute variable), augmented product moment matrix, autoassociative network, automatic network designer, b coefficients, back propagation, banner tables, bar dev plot, bar left y plot, bar right y plot, bar top plot, bar x plot, bar/column plots, 2d, bartlett window, batch algorithms in statistica neural networks, bayesian networks, best network retention, best subset regression, beta coefficients, beta distribution, bimodal distribution, bivariate normal distribution, blocking, bonferroni test, boundary case, box plot/means (block stats graphs), box plot/medians (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, cart, chaid, canonical correlation, cartesian coordinates, casewise md deletion, categorical predictor, categorized 3d scatterplot (ternary graph), categorized contour/areas (ternary graph), categorized contour/lines (ternary graph), 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, categorizing, cauchy distribution, censoring (censored data), censoring, left, censoring, multiple, censoring, right, censoring, single, censoring, type i, censoring, type ii, characteristic life, chernoff faces (icon plots), chi-square distribution, circumplex, city-block error function in neural networks, city-block (manhattan) distance, 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, conditioning (categorizing), confidence interval, confidence interval for the mean, confidence limits, confusion matrix in neural networks, conjugate gradient descent, contour plot, contour/discrete raw data plot, control, quality, cook's distance, correlation (pearson r), correlation, intraclass, correspondence analysis, cpk, cp, cr, cross entropy in neural networks, cross verification in neural networks, cross-validation, crossed factors, crosstabulations, dffits, doe, dv, daniell (or equal weight) window, data mining, data reduction, data rotation (in 3d space), data warehousing, degrees of freedom, deleted residual, delta-bar-delta, denominator synthesis, dependent t-test, dependent vs. independent variables, derivative-free function minimization algorithms, design matrix, design, experimental, desirability profiles, detrended probability plots, deviance, deviance residuals, deviation, deviation plot (ternary graph), deviation plots, 3d, differencing (in time series), dimensionality reduction, discrepancy function, discriminant function analysis, distribution function, double-y histograms, double-y line plots, double-y scatterplot, drilling-down (categorizing), duncan's test, dunnett's test, erp, effective hypothesis decomposition, efficient score statistic, ellipse, prediction area and range, endogenous variable, enterprise resource planning (erp), enterprise spc, enterprise-wide software systems, 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, estimable functions, euclidean distance, exogenous variable, explained variance, exponential distribution, exponential family of distributions, exponential function, exponentially weighted moving average line, extrapolation, extreme value distribution, extreme values (in box plots), f distribution, fact, factor analysis, fast analysis of shared multidimensional information (fasmi), feedforward networks, fisher lsd, fixed effects (in anova), free parameter, frequencies, marginal, frequency scatterplot, function minimization algorithms, grnn (generalized regression neural network), gamma distribution, gamma coefficient, gaussian distribution, general anova/manova, general linear model, generalization in neural networks, generalized inverse, generalized linear model, generalized regression neural network (grnn), genetic algorithm, genetic algorithm input selection, geometric distribution, gompertz distribution, gradient, gradient descent, gradual permanent impact, group control charts, grouping (categorizing), grouping variable, groupware, htm, 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 - box plots, histograms, 3d - contour plot, histograms, 3d - contour/discrete, histograms, 3d - spikes, histograms, 3d - surface plot, histograms, 3d bivariate, hollander-proschan test, hooke-jeeves pattern moves, hyperbolic tangent (tanh), hyperplane, hypersphere, iv, 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 t-test, independent vs. dependent variables, industrial experimental design, interactions, interpolation, interval scale, intraclass correlation coefficient, invariance under change of scale (ics), invariance under a constant scale factor (icsf), isotropic deviation assignment, item and reliability analysis, jpeg, jpg, jogging weights, johnson curves, k-means algorithm, k-nearest algorithm, kendall tau, kernel functions, kohonen networks, kohonen training, kolmogorov-smirnov test, kronecker product, kruskall-wallis test, kurtosis, lowess smoothing, lack of fit, lambda prime, laplace distribution, latent variable, layered compression, learning rate in neural networks, least squares (2d graphs), least squares (3d graphs), least squares estimator, least squares means, left censoring, levenberg-marquardt algorithm, levene's test for homogeneity of variances, leverage values, life table, life, characteristic, lilliefors test, line plots, 2d, line plots, 2d (case profiles), line plots, 2d - aggregrated, 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 units, lines (icon plot), lines (matrix plot), lines sequential/stacked plot, link function, local minima, locally weighted (robust) regression, log-linear analysis, log-normal distribution, logarithmic function, logistic distribution, logistic function, logit regression and transformation, lookahead in neural networks, loss function, loss matrix, manova, md (missing data), mpatt bar, mahalanobis distance, manifest variable, mann-scheuer-fertig test, marginal frequencies, matching moments method, matrix collinearity, matrix ill-conditioning, matrix inverse, matrix plots, matrix plots - columns, matrix plots - lines, matrix plots - scatterplot, matrix rank, matrix singularity, maximum likelihood loss function, maximum likelihood method, maximum unconfounding, mean substitution of missing data, mean, geometric, mean, harmonic, mean/s.d. algorithm in neural networks, means, adjusted, means, unweighted, method of matching moments, minimax, minimum aberration, mining, data, missing values, mixed line sequential/stacked plot, mixed step sequential/stacked plot, monte carlo, multi-way tables, multicollinearity, multidimensional scaling, multilayer perceptrons, multimodal distribution, multinomial distribution, multinomial logit and probit regression, multiple censoring, multiple dichotomies, multiple histogram, multiple line plots, multiple r, multiple regression, multiple response variables, multiple scatterplot, multiple-response tables, multiplicative season, damped trend, multiplicative season, exponential trend, multiplicative season, linear trend, multiplicative season, no trend, n-in-one encoding, negative exponential (2d graphs), negative exponential (3d graphs), neighborhood in neural networks, nested factors, nested sequence of models, neural networks, neuron, newman-keuls test, noise addition in neural networks, nominal scale, nominal variables, non-outlier range, nonlinear estimation, nonparametrics, nonseasonal, damped trend, nonseasonal, exponential trend, nonseasonal, linear trend, nonseasonal, no trend, normal distribution, bivariate, normal fit, normal probability plots, normal probability plots (computation note), normality tests, normalization, odds ratio, on-line analytic processing (olap), one-off in neural networks., one-sample t-test, one-of-n encoding in neural networks., one-way tables, operating characteristic curves, ordinal multinomial distribution, ordinal scale, outer arrays, outliers (in box plots), overfitting, overlearning in neural networks., overparameterized model, png files, pnn (probabilistic neural networks), press statistic, psp (post synaptic potential) function, pairwise deletion of missing data vs. mean substitution, pairwise md deletion, pareto distribution, part correlation, partial correlation, partial least squares regression, parzen window, pearson correlation, pearson curves, pearson residuals, penalty functions, percentiles, pie chart - counts, pie chart - multi-pattern bar, pie chart - values, pies (icon plots), poisson distribution, polygons (icon plots), polynomial, portable network graphics files, positive correlation, post synaptic potential (psp) function, post hoc comparisons, power goal, ppk, pp, pr, prediction interval ellipse, prediction profiles, predictive mapping, principal components analysis, prior probabilities, probabilistic neural networks (pnn), probability plots - detrended, probability plots - half-normal, probability plots - normal, probability-probability plots, probability-probability plots - categorized, probit regression and transformation, process analysis, process capability indices, process performance indices, profiles (icon plots), profiles, desirability, profiles, prediction, pruning (in classification trees), pseudo-inverse algorithm, pseudo-components, pure error, quest, quadratic, quality, quality control, quantile-quantile plots, quantile-quantile plots - categorized, quantiles, quartile range, quasi-newton method, quick propagation, rms (root mean squared) error, rmsse, radial basis functions, random effects (in mixed model anova), range ellipse, range plots - boxes, range plots - columns, range plots - whiskers, rank, rank correlation, ratio scale, raw data plots, 3d - contour/discrete, raw data plots, 3d - spikes, raw data plots, 3d - surface plot, raw data, 3d scatterplot, 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, response surface, right censoring, robust locally weighted regression, root mean square standardized effect, rosenbrock pattern search, rotating coordinates, method of, runs tests (in quality control), s.d. ratio, sofms (self-organizing feature maps; kohonen networks), spc, statistica enterprise-wide spc system, statistica enterprise-wide system, scalable software systems, scaling, scatterplot, scheffe's test, score statistic, scree plot, scree test, semi-partial correlation, sequential contour plot, 3d, sequential surface 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, shapiro wilk's w test, shewhart control charts, short run control charts, shuffle data in neural networks, shuffle, back propagation in neural networks, sigma restriced model, sigmoid function, signal detection theory, simplex algorithm, single censoring, singular value decomposition, skewness, slicing (categorizing), smoothing, softmax, space plots 3d, spearman r, 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 error of the proportion, standard residual value, standardization, standardized dffits, standardized effect (es), stars (icon plots), stationary series (in time series), statistical power, statistical process control (spc), statistical significance (p-level), steepest descent iterations, steps, stepwise regression, stopping conditions, stopping rule (in classification trees), stub and banner tables, student's t distribution, studentized deleted residuals, studentized residuals, sum-squared error function, sums of squares (type i, ii, iii (iv, v, vi)), sun rays (icon plots), supervised learning in neural networks, suppressor variable, surface plot (from raw data), survival analysis, survivorship function, sweeping, symmetric matrix, symmetrical distribution, thaid, tapering, tau, kendall, ternary graph, 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, threshold, time series, time-dependent covariates, tolerance (in multiple regression), topological map, trace plots, 3d, transformation (logit regression), transformation (probit regression), trellis graphs, trimmed means, tukey hsd, tukey window, two-state in neural networks, type i censoring, type i error rate, type i, ii, iii (iv, v, vi) sums of squares, type ii censoring, unconfounding, maximum, unequal n hsd, uniform distribution, unimodal distribution, unit penalty, unsupervised learning in neural networks, unweighted means, variance components (in mixed model anova), variance inflation factor (vif), voronoi, voronoi scatterplot, wald statistic, warehousing, data, weibull distribution, weigend regularization, weighted least squares, wilcoxon test, win frequencies in neural networks, wire, yates corrected chi-square, year 2000 compatibility, control group, g2 inverse, n point moving average line, numerical expression, p-level (statistical significance), r (pearson correlation coefficient), t distribution (student's), two-way table