- Absorbing factor – Autocorrelation
- Autoregressive – Canonical variate
- Centroid – Confounding
- Continuous distribution – d.f.
- Degrees of freedom – e.f.
- e.s.e – Factorial limit
- Fitted configuration – Hierarchical clustering
- Imaginary – Least-squares scaling factor
- Left singular vector – m.v.
- Mahalanobis distance – Negative binomial index
- Neyman type A – Orthogonal
- Orthogonal rotation – Poisson-Pascal
- Polynomial – Quad
- Quantile – Residual
- Response – Semivariance
- Semivariogram – Spectral analysis
- Spectral decomposition – Submodel
- Sum of squares – v.r.
- Variance – Yates effect
Terminology explains some of the mathematical and statistical terms used in the Genstat output: Absorbing factor, Accumulated analysis of deviance, Accumulated analysis of variance, Added factor, Alias, Analysis of covariance, Analysis of variance, Ante-dependence, ARIMA, Autocorrelation, Autoregressive, Axes, Balanced design, Basic factor, Binomial distribution, Bernoulli distribution, Binomial totals, Bit pattern, Block-factor, Canonical variate, Centroid, Class predictor, Classification set, Clustering, Combined means, Combined effects, Combined estimate, Communalities, Complex latent root, Confounding, Continuous distribution, Contrast, Correlation, cov. e.f., Covariance efficiency factor, Cross correlation, Cub, Cut-point, d.f., d.d.f., Degrees of freedom, Dendrogram, Design key, Deviance, Deviations, Discrete distribution, Dispersion parameter, Distance matrix, Distribution, e.f., e.s.e., Effect, Effective d.f., Efficiency factor, Eigenvalue, Eigenvector, Estimate, F pr., Factor rotation, Factorial limit, Fitted configuration, Fitted value, Fixed model, Fixed configuration, Fourier transformation, Generalized additive model, Generalized linear model, Grand mean, Heterogeneity, Hierarchical clustering, Imaginary, Information summary, Initial classification, Innovation variance, Kriging, Kurtosis, Lag, Latent root, Latent vector, Least-squares scaling factor, Left singular vector, Leverage, Lin, Linear parameter, Link function, Loadings, Log series, Lognormal, m.s., Mean square, m.v., Mahalanobis distance, Maximal predictive criterion, Median, Minimum spanning tree, Moving-average, Multidimensional scaling, n.d.f., Negative binomial, Negative binomial index, Neyman type A, Noise model, Non-hierarchical clustering, Non-orthogonal, Nugget variance, Offset, Ordered categorical data, Ordinal model, Orthogonal, Orthogonal rotation, Partial aliasing, Partial confounding, Pedigree, Percentage variance accounted for, Periodogram, Poisson, Poisson index, Poisson-log-Normal, Poisson-Pascal, Polynomial, Prediction, Principal component, Principal components analysis, Principal component score, Principal coordinate, Principal coordinates analysis, Procrustes rotation, Pseudo-factor, Quad, Quantile, Quart, Quartile, Random coefficient model, Random model, Randomization, Reduced similarity matrix, rep., Replication, Residual, Response, Response variate, Restriction, Right singular vector, Rotated factor, s.e., s.e.d., s.s., Sample statistic, Semivariance, Semivariogram, Separate nonlinear, Sill variance, Similarity matrix, Singular value, Singular value decomposition, Skewness, Smoothed, Smoothing spline, Spectral analysis, Spectral decomposition, Spline, Spline model, ss.div., Standard error, Standard error of difference, Standardized residual, Stratum, Stratum variance, Submodel, s.s., Sum of squares, t prob, Trace, Transfer-function model, Trellis plot, Two-matrix latent decomposition, Unbalanced design, *units*, Unsymmetric matrix decomposition, v.r., Variance ratio, Variance, Variance component, Variogram, Wald statistic, wt.rep., Y-effect, Yates effect.
See also
- Glossary for explanations of Genstat terminology