A B C D E F G H I J K L M N O P Q R S T U V W Z

A

• ABCD design—screening design for mixtures, DOE, Mixture Design
• Accelerated failure—parametric survival models, Fit Model > Parametric Survival
• actuarial life table templates included (see templates)
• added-variable plot (see leverage plot)
• adjusted means (see least squares means)
• A-efficiency (D-optimal designs), DOE, Custom Design
• AIAG labels—variability chart option, Variability/Gage Chart
• AIC, Akaike’s ‘A’ Information Criterion, Fit Model Stepwise
• Alias matrix—shows bias from two-factor interactions not in the model, Custom Design DOE
• aliasing structure table—shows confounding patterns
• all possible regressions—Fit Model Stepwise
• alpha level specification (optional in many platforms)
• analysis of covariance—same slopes, Fit Model SLS
• analysis of covariance—separate slopes, Fit Model SLS
• analysis of loglikelihood, likelihood ratio—Chi-square test of how well categorical model fits, Fit Y by X categorical, Fit Model Nominal or Ordinal Logistic
• analysis of variance (general)—profile, contrasts, custom tests, crossed, nested, polynomial, surface and random effects, LSMeans, student’s t and Tukey tests for multiway ANOVA, mixed models (with no assignable covariance structure) using REML estimation, Fit Model
• analysis of variance (one-way)—F test (or t-test if there are only two levels), Fit Y by X oneway
• analysis of variance ( non-parametric)—Wilcoxon, Median and Van der Waerden tests, Fit Y by X oneway
• animation of statistical graphics—JSL application (see scripting language, some scripts built in
• ANOVA (see analysis of variance), Fit Y by X, Fit Model
• ANCOVA (see analysis of covariance), Fit Model
• AR coefficients plot and values—diagnostic for time series modeling, Modeling > Time Series
• ARIMA and seasonal ARIMA forecasting (see time series modeling and forecasting), Modeling > Time Series
• attribute charts—p, np, c, and u control charts, Control Chart
• attribute gage charts
• augmented designs—replicate, add center or axial points, foldover designs, DOE, Augment Design
• autocorrelation—Durbin Watson test for autocorrelation, Fit Model SLS
• autocorrelation plots and values—diagnostic for time series modeling, Modeling > Time Series
• auto fill data tables with constant, pattern or random data
• automatic derivatives (formula displayed)—nonlinear regression, Modeling > Nonlinear
• automation of JMP—most of JMP can be driven by OLE automation or the JMP Scripting Language (JSL)
• average linkage—cluster method, Multivariate Methods > Cluster
• axial points—response surface designs or augmented, DOE, Response Surface Design
• axis scaling—option to scale X and Y in most plots
• axis scaling—option for central composite design, DOE, Response Surface Design

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B

• backpropogation—Modeling > Neural Net
• bar chart—Chart option
• Bartlett’s test for homogeneity of variance, Fit Y by X oneway
• Bayes plot (Box-Meyer)—screen for active effects in regression model, Fit Model
• Bayesian D-optimal design—DOE, Custom Design
• beta fit (see fitting distributions)
• between& within charts (see presummarize charts)
• Bias report—Variability/Gage Chart
• biplot (Gabriel)—3-D plot of principal components and variables, k-means clusters, Spinning Plot, Multivariate Methods > Cluster
• binomial fitting—Distribution
• bivariate fitting—fit mean, linear, polynomial, transformed values, spline, density ellipses, orthogonal, other (regression and curve fitting), Fit Y by X
• Box-Behnken—(DOE), Response Surface Design
• Box-Cox power transformation—screening designs and factor profiling, Fit Model
• Box-Jenkins time series analysis, Modeling > Time Series
• Box-Meyer Bayesian analysis (Bayes plot)—Fit Model
• Box-Wilson response surface design (DOE), Response Surface Design
• box plot—individual distribution (see quantile box plot and outlier (box & whiskers) box plot), Distribution
• box plot option—displays sample distributions on means, Fit Y by X oneway, Control Charts
• Brown-Forsythe test for homogeneity of variance, Fit Y by X oneway
• Brown-Mood k-sample median test nonparametric test to compare group means, Fit Y by X oneway
• By-group processing—process by groups, graphs and analyses appear in one window, no presorting data

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C

• calculator—(formula editor)
• calibration—see inverse prediction and orthogonal regression
• canonical correlation—save canonical Ys as a new data table column, Fit Model Manova
• canonical centroid plot—shows points and multivariate means in the two dimensions that best separate the groups, Fit Model Manova
• capability analysis—long term and short term indices, out of spec as percent and as parts per million, (PPM), Shewhart chart, histogram, quantile plot, one or more capability estimates s: long term, specified, short term grouped by fixed subgroup size, short term grouped by column, Sigma Quality (also call Process Sigma) included as a hidden column in report, Distribution
• categorical analysis, two-way—contingency table for two categorical variables, two-way frequency table with count, total%, row%, col%, expected, deviation, and cell Chisq, Fit Y by X categorical
• categorical model fit—nominal or ordinal response, analysis of loglikelihood Chi-square, Fit Model
• cause-and-effect diagrams (see Diagram)
• cell plot—displays data table cells as a matrix of rectangular colors, Cell Plot
• censored data—right and left censoring, arbitrary censoring, survival analysis, nonlinear fitting, Survival and Reliability, Modeling > Nonlinear
• central composite designs, DOE, Response Surface Design
• centroid method—Multivariate Methods > Cluster
• centroid plot—Fit Model MANOVA
• chart—stack or overlay, bars, lines, needles; horizontal, vertical, pie chart, means with standard error bars
• Chi-square tests—fitted distributions, Distribution
• Chi-square tests—for general categorical response models, Wald and Likelihood ratio, Fit Model
• Chi-square nonparametric tests—Wilcoxon, Median, Van der Waerden, Fit Model
• Chi-square statistic—Likelihood Ratio, Pearson’s for two-way tables, Fit Y by X categorical
• cluster analysis—hierarchical, k-means, normal mixtures clustering, geometric scale, color map, dendrogram, Self Organizing Maps (SOMS), save cluster hierarchy, biplots available for k-means cluster, Multivariate Methods > Cluster
• Cochran-Mantel-Haenszel for testing association of X and Y variables across groups, Fit Y by X categorical
• coefficient of variation (CV)— hidden column in Moments table and in REML and EMS results, available in data table using the Summary command, Distribution
• collinearity—leverage plots show when model factors are linear combinations of others, Fit Model SLS
• comparison circles—graphically shows one-way multiple comparisons, Fit Y by X Anova
• competing risk analysis, competing causes analysis or recurrence analysis—Survival and Reliability
• complete linkage clustering method—Multivariate Methods > Cluster
• concatenate—append JMP data tables end to end
• confidence curves—on scatterplot (individual and mean) for regression fits, optionally specify alpha level, Fit Y by X bivariate
• confidence limits, individual and mean—for mean and standard deviation, save as new data table column, for inverse prediction, for nonlinear fitting
• confounding—DOE aliasing report, Screening Design
• confounding—shows if terms in a model are linearly related in DOE, singularity details table in Fit Model
• contingency tables—see categorical analysis, two-way
• contour plots—equal probability contours from 2-dimensional density estimation, Fit Y by X bivariate
• contour plots—contours with labels, legends, color fills, predicted response within a ternary plot, response surface model effects, Contour Plot
• contour profiler (overlayed contour plots)—Fit Model SLS, also Graph > Contour Profiler
• contrasts—test a linear combination of parameters in a general linear model, Fit Model SLS
• control charts—Shewhart charts (Mean, R, S, and Individual Measurement charts), UWMA and EWMA moving average charts, Cusum (Cumulative Sum) charts with V mask, charts for attribute data, p, np, c and u, Presum, Run, Levey-Jennings, Control Charts
• Cook’s D—influence statistics, save as a new data table column, Fit Model SLS
• coordinate exchange algorithm—create custom D-optimal designs, DOE, Custom Design
• Correlation—bivariate scatterplot with density ellipses and report, Fit Y by X bivariate
• correlation—many variables, pairwise report with significance probabilities, histogram of correlations (Pearson’s R, Spearman’s Rho, Kendall’s Tau, Hoeffding’s D), inverse correlation, partial correlation, scatterplot matrix with density ellipses, Multivariate Methods > Multivariate
• correspondence analysis—graph for categorical model shows which rows and columns are similar in a two-way contingency, Fit Y by X categorical
• Cotter designs—DOE, Screening Design
• covariance—covariance matrix, Multivariate Methods > Multivariate
• Cox proportional hazards model, Fit Model, Survival/Reliability > Proportional Hazard
• Cp—selection of stepwise model (Mallow’s Cp) Fit Model Stepwise
• Cramer-von Mises W statistic— goodness of fit statistic for one-way distribution fitting, Distribution
• Cronbach’s alpha and standardized alpha—based on average correlation of items (item reliability analysis), Multivariate Methods > Multivariate
• crosstabs—see categorical analysis, two-way
• cube plot—DOE, Screening Design
• cumulative distribution function (CDF) plot, for distribution fits, Distribution
• cumulative logistic probability plot—logistic regression, Fit Y by X logistic
• cumulative sum chart—Cusum control chart with V mask, Control Charts
• curve fitting—bivariate fitting of line, polynomials, spline, and density ellipses, curves from a nonlinear fit, smooth curve fitting of histograms ° distribution fitting of histograms, Fit Y by X bivariate
• Custom Design—create custom designs for both standard and nonstandard design situations, DOE, Custom Design
• custom loss function—maximum likelihood estimation in nonlinear regression, Modeling > Nonlinear
• custom tests—construct specialized tests for general linear model hypotheses, Fit Model SLS

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D

• data entry—key in data, paste from clipboard, import data, access other databases
• D-efficiency, D-optimal designs—DOE, Custom Design
• decision tree—see Partition
• DPU—defect per unit analyses calculate and compare defect rates across and within groups, Graph > pareto plot
• Deming regression—see orthogonal regression
• dendrograms—cluster diagram, Multivariate Methods > Cluster
• density ellipse with two variables—visualization of correlation, Fit Y by X bivariate
• density ellipses, scatterplot matrix for many variables— visualization of correlation, Multivariate Methods > Multivariate
• density estimation—distribution fit on histogram, equal probability contours on bivariate scatterplot, Distribution and Fit Y by X bivariate
• derivatives—nonlinear regression, Modeling > Nonlinear
• DOE (Design of Experiments)—commands build experimental designs for almost every situation
• desirability profiling—prediction profile, helps visualize and optimize the response at different factor settings, optimize screening, response surface, and mixture designs, DOE, Custom Design and Fit Model SLS
• Diagram—produces ishikawa charts, fishbone charts, cause-and effect diagram, Diagram
• discriminant analysis—compute discriminant scores, classify points, save discriminant scores, optional stepwise selection, canonical plots, Multivariate Methods > Discriminant
• distribution fitting—fitting, graphing, capability analysis, quantile plots for distributions: Beta, Normal, Lognormal, 2 & 3 parameter Weibull, Extreme Value, Gamma and Exponential, Binomial, Poisson, p value and power animations, tolerance Intervals computed, Distribution
• Duncan’s multiple comparison test—not available, see Tukey-Cramer
• Dunnett’s test—tests multiple comparison to a control group, Fit Y by X one-way
• Durbin Watson test—test that residuals are autocorrelated, Fit Model SLS

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E

• E matrix—multivariate models Fit Model Manova
• ED50 & LD50—nth percentile with confidence limit using logistic regression and inverse prediction, Fit Model SLS and Fit Y by X bivariate
• editing table—standard Edit Menu commands
• effect screening—scaled estimates, normal plot, Bayes plot, Pareto plot, Fit Model SLS
• eigenvalues, eigenvectors—Fit Model SLS, response surface analysis
• ellipses—bivariate density, Fit Y by X and Multivariate Methods > Multivariate
• errors in measurement (see orthogonal regression)
• EWMA control chart—guards against small shifts in sample means, quality control, Control Chart
• Expected Mean Squares (EMS)—Fit Model SLS
• experimental design—see DOE
• exponential exploratory plot—Survival and Reliability
• exponential fit — fitting distributions, Distribution
• exponential model fitting—nonlinear regression with loss function, Modeling > Nonlinear
• exponential smoothing time series forecasting— Modeling > Time Series
• exponential survival curve analysis (see survival analysis)
• export JMP tables (Linux)— Save As command for tab delimited text file, SAS transport, Open Office Spreadsheet
• export JMP tables (Macintosh)— Save As command for tab delimited text file, SAS transport files, Excel file
• export JMP tables (Windows)—Save As command for tab delimited text file, SAS transport, SAS datasets, JMP file, Excel, ODBC compliant package and Access
• extreme value distribution fitting—nonlinear regression with loss function, Modeling > Nonlinear
• extreme vertices design—DOE, range and linear constraints, general constraints with JSL, Mixture Design

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F

• F test for all analyses where appropriate
• factor analysis—little jiffy factor analysis (Kaiser), Spinning plot and Multivariate Methods > Multivariate platforms
• factorial designs—fractional factorial, full factorial, blocking factor, Full Factorial Design
• failure-plot analysis—univariate survival analysis, Survival and Reliability .> Survival/Reliability
• Fieller’s theorem—confidence limits for inverse prediction, Fit Model
• fishbone chart—Diagram
• Fisher’s Exact test—for two-way contingency tables, Fit Y by X categorical
• Fisher’s Kappa—test for white noise, see Spectral Density, Modeling > Time Series
• fitting distributions—distribution curve fits and parameter estimates for continuous one-way data, includes Normal, Lognormal, Poisson, 2 & 3 parameter Weibull, Extreme Value, Gamma, Beta, Exponential and a nonparametric density smoother, Distribution
• fitting personalities—standard least squares, stepwise, Manova, loglinear variance, nominal logistic, ordinal logistic, proportional hazard, parametric survival, Fit Model
• fitting transformed data—Fit Special fits natural log, square root, square, reciprocal, and exponential transformations of either or both Y and X variables, Fit Y by X bivariate
• forecasting—Modeling > Time Series
• fractional factorial designs—DOE, Custom Design and Screening Design
• frequency counts—one-way and two-way cross-tabulation table with Chi-square tests, Distribution and Fit Y by X categorical
• frequency counts—column in data table produced by Tables > Group/Summary command
• full factorial design—DOE, Full Factorial Design

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G

• Gabriel biplot—3-D plots of principal components and variables, Spinning Plot
• Gage R&R report—for two factor crossed models, Graph > Variability/Gage Chart
• Gamma fit (see fitting distributions)
• G-efficiency (D-optimal designs)—DOE, Custom Design
• Generalized Linear Models—regression analysis for Poisson, Binomial, Normal and Exponential distributions with a variety of link functions. Overdispersion adjusted likelihood ratio tests and confidence intervals are also supported.
• goodness of fit—Chi-square statistic based on proportions, see lack of fit test
• goodness of fit tests for one-way distribution fitting— Shapiro-Wilk and KSL tests for Normal, KSL for Lognormal and Exponential, Cramer-von Mises W for Weibull and Extreme Value, Distribution
• Greenhouse-Geisser adjustment—multivariate model fit adjustment, Fit Model Manova
• grouping variable option in many platforms

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H

• H matrix—multivariate models, Fit Model Manova
• heat maps (see cell plots)
• heteroschedasticity—group variances differ, Fit Y by X oneway
• hierarchical clustering, Multivariate Methods > Cluster
• hierarchy chart—Diagram
• histograms—linked to data table, summary statistics, moments report, count axis, prob axis, error bars, counts and percents on bars, Distribution
• Histogram borders—option in any Fit Y by X bivariate plot
• Hoeffding’s D—nonparametric correlation, Multivariate Methods > Multivariate
• homogeneity of variances— O’Brien’s, Brown-Forsythe, Levene’s and Bartlett’s, Fit Y by X oneway
• Hotelling-Lawley Trace— approximate F test for multivariate analysis of variance, Fit Model Manova
• Hotelling’s T2—Fit Model, Manova
• Hsu’s MCB test—multiple comparison that tests to a selected ‘best’ group—Fit Y by X one-way
• Huynh-Feldt—adjusts degrees of freedom, Fit Model Manova

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I

• import data (Linux)—Open command for JMP data tables, JMP journals, JSL scripts, JMP reports, text files, Open Office Spreadsheet files; Download files from website and open any database having UNIX ODBC driver
• import data (Macintosh)—Open command for JMP data tables, JMP journals, JSL scripts, FACS files, Excel files, text files, SAS transport files, and SAS data sets
• import data (Windows )—Open command for JMP tables, JMP journals, JSL scripts, SAS data sets, SAS transport files, automatic format discovery, Microsoft® Excel and Microsoft® Access files, dBase® files, FoxPro® files, and any other ODBC supported databases.(see also ODBC), Download files from website
• individual measurement—Control Chart
• inertia—correspondence analysis quantity Fit Y by X categorical analysis
• influence statistics—Cook’s D regression diagnostic, Fit Model SLS
• instrument data source for collecting real-time data
• Ishikawa charts—Diagram
• interaction plots—matrix of interaction profile plots of all two factor interactions, Fit Model SLS
• interaction plot matrix— matrix of two factor interactions in DOE, Screening Design
• interaction tests—Test Slices tests many main effects and interactions at one time, Fit Model SLS
• inverse correlation matrix—Multivariate Methods > Multivariate
• inverse prediction (calibration)— predict X for a given response, Y , Fit Model SLS
• I-optimality— DOE, Custom Design
• Item Analysis—score tests with the Item Response Theory (IRT), Multivariate Methods > IRT
• iteratively reweighted least squares (IRLS)—nonlinear regression, Modeling > Nonlinear

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J

• jackknifed Mahalanobis distance plot— Multivariate Methods > Multivariate
• jittered points—outlier box plot, Distribution
• join (merge)—join tables side by side, join by key fields, Cartesian join (all levels of table1 with all levels of table2, Tables menu
• journal—capture JMP analysis into an editable window
• JSL—JMP Scripting Language (see rerun analysis and scripting language)
• JSL Editor—continuing enhancements

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K

• Kackar-Harville—standard errors in mixed models
• Kaplan-Meier life table analysis—Survival and Reliability > Survival/Reliability
• Kappa statistic—agreement statistic for two-way tables when there are equal levels in both variables, Fit Y by X categorical
• Kappa, Fisher’s—see Fisher’s kappa
• Kendall’s tau-b—nonparametric correlation, Multivariate Methods > Multivariate
• kernel smoothing—two-way nonparametric density contours for scatterplots Fit Y by X bivariate
• Kenward-Roger—tests on fixed effects in mixed models
• K-means clustering—iterative process to form the number of user-specified clusters, optional parallel coordinate plot, Multivariate Methods > Cluster
• Kruskal-Wallis test—nonparametric test of k sample means , Fit Y by X oneway
• KSL (Kolmogorov-Smirnov-Lilliefors) test— nonparametric goodness of fit to normal distribution for large sample size, n>2000, Shapiro-Wilk test statistic for smaller samples, Lognormal, and Exponential distributions, Distribution
• Kurtosis—Distribution

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L

• L18 and L36—DOE, Screening Design
• labels—identify data points in any plot with values in one or more columns
• lack of fit tests—for linear models when appropriate
• Latin Hypercube—method of generating a Space Filling Design, DOE, Space Filling Design
• lattice mixture designs—DOE, Mixture Design
• layout command—Edit menu command captures results of a JMP analysis, layout results are editable
• least squares fitting—standard fitting method for all linear models
• least squares means comparisons for multi-way layouts—Tukey’s HSD for multiple comparisons and Student’s t for pairwise comparisons, Fit Model SLS
• left-censored survival models (see tobit model)
• Lenth’s method, pseudo-standard error—method fits line to normal quantile points of parameter estimates in regression analysis, Fit Model SLS
• letter report (presentation of multiple comparisons results), Fit Model SLS
• Levene’s test for homogeneity of variance, Fit Y by X oneway
• leverage plots—effect test graph of a partial F test, Fit Model SLS
• Levey-Jennings chart type, Control Chart
• life tables (actuarial) templates included in sample data library
• life tables (product-limit or Kaplan Meier)—Survival and Reliability > Survival/Reliability
• Likelihood Ratio Chi-square test , two-way contingency table analysis, logistic models, Fit Y by X categorical and Fit Model Nominal or Ordinal Logistic
• Lilliefors confidence bands—normal quantile plot, Distribution
• line chart—single or overlay plots, points connected or unconnected, needle plot, linear or log scales, Chart
• linearity study—graphs linearity and summarizes linearity of bias in variability charts, Variability/Gage Chart
• logarithmic axes—overlay plot and bivariate plot
• logistic regression— analysis of loglikelihood Chi-square statistic, save probability scores, Wald’s and Likelihood Ratio Chi-square, Fit Y by X logistic and Fit Model Nominal or Ordinal Logistic
• log-linear model—see logistic regression
• loglogistic distribution model fitting—nonlinear regression with appropriate loss function (see also loss function templates)
• lognormal fits—see fitting distributions
• lognormal survival curve analysis—Survival and Reliability > Survival/Reliability
• log-rank test—Survival and Reliability > Survival/Reliability
• loss function templates—for exponential, extreme value, loglogistic, lognormal, normal, tobit, and Weibull distributions, used with arbitrary censoring
• LSD (Least Significant Difference)—difference in means that is significant at a given p-value in multiple comparison test tables, Fit Y by X oneway
• LSMeans—test for ANOVA effects, Fit Model SLS
• LSN (Least Significant Number)— sample size determinations shown in power calculations results, Sample Size and Power (DOE menu)
• LSV (Least Significant Value)— parameter determinations, shown in power calculations results, Sample Size and Power (DOE menu)

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M

• M Matrix—Fit Model Manova
• Mahalanobis distance outlier plot—distance of point from n-dimensional centroid of points, Multivariate Methods > Multivariate
• Mallow’s Cp—stepwise selection criterion, Fit Model SLS
• Mann-Whitney U test—same as Wilcoxon 2-sample or Kruskal-Wallace k-sample, Fit Y by X oneway
• MANOVA and MANCOVA—Multivariate Analysis of Variance, Multivariate Analysis of Covariance, Fit Model Manova
• Mantel-Haenszel test—tests for association between Y and X classification variables across categories, Fit Y by X categorical
• marginal means—Fit Model SLS
• Mauchley criterion—see sphericity test
• matched pair analysis—paired t-tests and grouped data with two repeated measures, Matched Pairs
• matrix algebra—available in scripting language (JSL)
• maximize desirability—set desirability functions to identify best process variable settings, see desirability functions and prediction profiler
• maximum likelihood—nonlinear regression, loss function is a negative loglikelihood, Fit Model Manova
• Maximum r-square—lack-of-fit test shows maximum possible r-square, Fit Model SLS
• MCF plot—mean cumulative function, Survival/Reliability > Recurrence Analysis
• mean—estimates with confidence interval
• mean control chart for variables— quality control, Control Chart
• mean equal to a given value—z test, t test, signed rank test, Distribution
• means across groups—in data table using Group/Summary command
• means diamonds—shows mean and 95% confidence interval for each group, Fit Y by X oneway
• means with error bars—means optional with one standard error above and below the mean, option for std. dev. lines, Fit Y by X oneway
• means—single population, Distribution
• measurement regression—see orthogonal regression
• median—quantiles in Distribution and as data table column from Group/Summary command, shown on Fit Y by X oneway box plots
• median and % total summary statistics—given in JMP table produced by Group/Summary command
• median moving range charts (see Control Charts)
• median test—2-sample and Brown-Mood k-sample, Fit Y by X oneway
• minimum potential—spherical space filling design, DOE
• missing data pattern—table menu command to generate a JMP data table of missing data patterns
• mixed-level designs—DOE, Custom Design
• mixed model— includes randomized complete block and incomplete block designs, split, strip, and split-strip plot designs, repeated measures designs, random effect models, uses REML estimation, and Kenward-Roger fixed effects tests, Fit Model SLS
• mixture designs—DOE, Mixture Design, Custom Design
• modeling type—modeling type (nominal, ordinal, or continuous) of variable defines method of analysis
• moments, descriptive statistics—Distribution or columns in data table produced by Group/Summary command
• mosaic plot—stacked bar chart of proportion levels for single variable or side-by-side for cross-tabulations, Distribution and Fit Y by X categorical analysis
• moving average analysis of time series—see time series modeling and forecasting
• moving average charts—UWMA and EWMA, Control Chart
• multi-var chart—shows variation over groups, Variability/Gage Chart
• multicollinearity—see collinearity
• multiple comparisons—one-way ANOVA, Student’s t, Tukey-Kramer, Dunnett’s test, Hsu’s MCB test, Fit Y by X oneway
• multiple regression—Fit Model SLS
• multivariate control charts—Multivariate
• multivariate techniques—MANOVA models, 3-D spinning plot, principal components, biplots, discriminant analysis, canonical correlation, cluster analysis, Item Analysis, Little Jiffy factor analysis, multivariate outlier plots, PLS (partial least squares)
• multivariate tests—Wilks’ Lambda, Pillai’s Trace, Hotelling-Lawley Trace, Rows Maximum root Criterion, Fit Model Manova

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N

• navigation—JMP Starter helps novice users find and launch correct platforms for analyses and graphics
• needle mean chart—Xbar (mean) control chart, Control Chart
• needle plot—line charts with lines replaced by needles from x-axis to points, Chart
• nested design analysis—Fit Model SLS
• Neural Net—neural net modeling using a single hidden layer with interactive crossvalidation, Modeling > Neural Net
• No-intercept models—mixture model analysis, Fit Model SLS
• nominal logistic regression—Fit Y by X or Fit Model
• nonlinear design—DOE for nonlinear models, DOE > Nonlinear Design
• nonlinear least squares fitting—Analyze > Modeling > Nonlinear
• nonparametric correlations— Kendall’s tau, Spearman’s rho, Hoeffding’s D, Multivariate Methods > Multivariate
• nonparametric density smoothing—density estimation of bivariate density, Fit Y by X bivariate
• nonparametric goodness of fit tests—KSL, Shapiro-Wilk and Cramer-von Mises W, tests fitted distribution, Distribution
• nonparametric one-way ANOVA and mean tests—Kruksal-Wallis (Wilcoxon), Median, Van der Waerden rank tests, Fit Y by X oneway
• normal curve—distribution fit, Distribution
• normal mixtures—robust, diagonal or full covariance
• normal plot—plots normal quantiles of parameter estimates, Fit Model SLS
• normal quantile plot (QQ plot)— plots normal standard line and deviations from normality, Distribution
• normality test—Shapiro-Wilk test, KSL test, Distribution
• np control chart for attributes—quality control, Control Chart

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O

• O’Brien’s test—homogeneity of variance, Fit Y by X oneway
• ODBC (Open DataBase Connectivity) compliance—to query and retrieve from databases
• odds ratios—see logistic regression
• ordinal logistic regression—Fit Y by X or Fit Model
• orthogonal array—DOE, Screening Design, Taguchi Design
• orthogonal designs—DOE, Screening Design, Response Surface Design
• orthogonal regression—line adjusted for variability in X as well as Y, Fit Y by X bivariate
• orthogonal t-test—tests parameter estimates after transformation makes them independent and indentically distributed, Fit Model SLS
• outlier (box & whiskers) box plot—Distribution
• outlier distance plot or jackknifed Mahalanobis distances—outlier detection, Multivariate Methods > Multivariate
• output and clipboard formats—text (RTF, HTML) graphics for windows (WMF, EMF, JPEG, PNG, PICT) graphics for Macintosh (PICT, JPEG, PNG (requires Quickload® 4.1 or higher))
• overlay plots—line and bar, double Y axes, plot y as a function of x, Overlay Plot

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P

• p chart—control chart for attributes, Control Chart
• pairwise correlation matrix—Multivariate Methods > Multivariate
• Parallel Plot—Graph menu platform that draws connected line segments across all responses for each row in the data table, Parallel Plot
• Parallel Coordinate Plots—option in K-Means Cluster report, Multivariate Methods > Cluster
• parameter estimates— given for all models, includes t-tests
• Pareto Chart— general, one-way comparative, two-way comparative histograms, Pareto Plot
• Pareto Chart— effects in a screening design model, Fit Model SLS
• partial autocorrelation plot and values—diagnostic for time series modeling, Modeling > Time Series
• partial correlation, group—Fit Model Manova
• partial correlation matrix—pairwise, Multivariate Methods > Multivariate
• partial least squares—predicting Ys with many Xs, often more Xs than observations, Multivariate Methods > PLS
• partial plot (see leverage plot)
• Partition—( CARTTM, CHAIDTM, C4.5, C5), recursively partitions data to predict a response, creates a tree of partitions, Modeling > Partition
• Pearson Chi-square test—two-way contingency table analysis, Fit Y by X categorical
• Pearson correlation coefficient—Fit Y by X categorical analysis and Multivariate Methods > Multivariate
• percentage profiles—Distribution and Fit Y by X categorical
• percent of total (% Total)—column in table produced by Group/Summary command, option in Chart
• phase control charts
• pie chart—Chart option
• Pillai’s trace—approximate F test for multivariate analysis of variance, Fit Model Manova
• Plackett-Burman two-level designs—DOE, Screening Design
• Plot—x-y plot of continuous data allows overlay of different y’s in the same plot
• PLS—see partial least squares
• Poisson fitting—Distribution
• Poisson regression—see Generalized Linear Models
• polynomial curve fitting—polynomial regression, Fit Y by X bivariate
• post-hoc comparisons—see multiple comparisons
• power analysis (prospective)— power calculations for single, two sample, and k-sample situations, one-variance, one-sample proportion, two-sample proportions, counts per unit, computes sigma quality level, Sample Size and Power (in DOE menu)
• power analysis (retrospective)—option for parameter estimates in Fit Model SLS
• power transformation—see Box-Cox power transformation
• predicted values—save with prediction formula as new column in the data table for most models
• profiler—shows predicted Y response for each combination of independent effects, includes desirability profiles, uses constraints in mixture design analysis, and can optimize desirability fuctions, Fit Model SLS
• prediction interval (Distribution)
• prediction variance profiler—shows the relative variance of prediction for each combination of independent effects, DOE, Custom Design
• Press statistic—helps assess the goodness of a linear model in Fit Model SLS
• Presummarnize control charts
• principal component analysis—Spinning Plot and Multivariate Methods > Multivariate
• probability plot—logistic regression, Fit Y by X logistic
• probability scores from logistic regression—save as a new data table column, Fit Y by X logistic and Fit Model Nominal or Ordinal Logistic
• probit model—categorical response, Fit Model Nominal or Ordinal Logistic, or Modeling > Nonlinear
• probit regression—see Generalized Linear Models
• Process Sigma (Sigma Quality)—in capability report of Distribution
• product-moment life table—also product-limit (Kaplan-Meier) survival analysis, univariate survival analysis, Survival and Reliability > Survival/Reliability
• profile plots of effects and interactions—Fit Model SLS
• profile-likelihood confidence intervals—for parameters corresponding to changes in the likelihood function, Modeling > Nonlinear, Modeling > Generalized Linear Models
• proportional hazards (Cox) model—semi-parametric survival regression model, Survival and Reliability > Proportional Hazards
• proportions, percentages—of counts in contingency table, Fit Y by X categorical
• p-value and power animations—accessible after testing a mean, animates changing sample size and alpha levels, Distribution

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Q

• QQ plot (Normal Quantile Plot)—plots normal standard line and deviations from normality, Distribution
• quality improvement—see control charts, capability indices, Pareto plot, Gage R&R and variability charts
• quantile box plot—Distribution
• quantile (normal quantile or QQ plot)— plots normal standard line and deviations from normality, Distribution
• quantiles- maximum, minimum, median and other percentiles—Distribution

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R

• R (range) control chart for variables—Control Chart
• R-square statistic—summary statistic for all analyses where appropriate
• random effects models—expected mean squares, variance component estimates, tests with respect to random effects, (see Mixed Model, REML), Fit Model SLS
• random row selection—for JMP and SAS data tables
• randomizing runs—available in DOE Custom Design
• rank tests—see nonparametric goodness-of-fit tests
• row exchange algorithm—in DOE the row exchange algorithm iteratively improves the random starting design, Custom Design
  real-time data acquisition—use custom JSL script
• recurrence analysis—analyzes multiple-recurrent data recurrent data as an MCF (Mean Cumulative Failure) plot and an event plot, Survival and Reliability > Recurrence Analysis
• recursive partitioning—see Partition
• regression and curve fitting—linear, polynomial with confidence limits, splines, density ellipses, fit each value, fit orthogonal, fit special, transformations of x and/or y variables, Fit Y by X bivariate
• regression—linear, multiple, ANOVA, MANOVA, MANCOVA, nonlinear, polynomial, proportional hazards (Box model), logistic, response surface, orthogonal (error in measurement), stepwise, matched pair, loglinear-variance models, Fit Model SLS
• Relative variance of prediction—table of precision of estimates for custom designs, DOE
• reliability analysis—see survival analysis
• REML (Restricted Maximum Likelihood) estimation—for variance component estimation (see mixed model)
• Remember Settings—DOE, option in prediction profiler remembers responses and desirability and reports on differences between various settings, Custom Design
• repeated measures design analysis—univariate (mixed models) with test for sphericity and two adjustments to degrees of freedom, (Greenhouse-Geisser and Huynh-Feldt , Fit Model Manova
• report table customization—show or hide columns, put borders around columns, sort by one of the columns, convert report to a JMP data table
• rerun analysis—script command on all platforms to rerun any analysis or graph, optionally save script to data and rerun
• residual plot (by predicted)—Fit Model SLS
• residual plot—Modeling > Time Series
• residuals—save as new data table columns
• residuals (studentized)—save as new data table columns
• resolution of a design—DOE, Screening Design
• response surface design—DOE, Response Surface Design
• response surface model analysis—contour plots, analysis with critical values and eigenstructure, Fit Model SLS
• right-censored survival model—Survival and Reliability
• robust regression—see iteratively reweighted least squares
• ROC (Receiver Operating Characteristic) curve for binary logistic regression—plots area under the curve of true positive by. false positive, Fit Y by X logistic
• Root Mean Square Error (RMSE)—all analyses where appropriate
• rotated components—varimax rotation of principal components, Spinning Plot or Multivariate Methods > Multivariate
• Roy’s maximum root—approximate F test for MANOVA models, Fit Model Manova
• Run Charts—Control Charts

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S

• S (standard deviation) control chart for variables— quality control, Control Chart
• sample size calculations (LSN)—shown in power calculations tables (see power analysis)
• SBC (Schwartz’s Bayesian Criterion)—goodness of fit, Modeling > Time Series
• scaled parameter estimates—for designed experiments and any multiple regression, Fit Model SLS
• scatterplots—bivariate plots, Fit Y by X bivariate or Overlay Plot
• scatterplot matrix—plots of all pairs of variables with density ellipses—Multivariate Methods > Multivariate
• scene 3D JSL commands—build your own 3D displays new Bbillboard text, Blendfunc, Pickcommand
• schematic plot— outlier box plot, Distribution
• scree plot—shows the sorted eigenvalues as a function of the eigenvalue index, Multivariate Methods > Multivariate
• screening designs—DOE, Screening Design
• scripting language—JSL, an extensive scripting language with commands to record, repeat, program, automate and customize tasks, do matrix algebra , animate graphs, write simulations and/or complex operations; JMPversion( ) command; enhanced show tree structure ( ) command
• Sequential Sum of Squares (Type 1 SS)—Fit Model
• Shapiro-Wilk test—nonparametric goodness of fit to test normality in smaller samples (N<2000), KSL test used for larger samples (see also goodness of fit one-way distribution fitting), Distribution
• Shewhart control chart (see control charts)—quality control, Control Chart
• signed rank test—nonparametric test for one sample test of Mean, Distribution
• simplex centroid mixture design—DOE, Mixture Design
• simplex lattice mixture design—DOE, Mixture Design
• simulation of fitted models—Profilers
• skewness—Distribution
• smoothing—(see spline fitting) also (see time series modeling and forecasting)
• smooth curve—see density estimation
• SOM—Self Organizing Map, Multivariate Methods > Cluster
• sort—sort a JMP data table by one or more columns, ascending or descending
• Space Filling Design—generate design when there is no random error, DOE, Space Filling Design
• Spearman’s rho—nonparametric correlation, Multivariate Methods > Multivariate
• specification limits, capability indices—quality control features in Distribution
• spectral density plots—spectral density by. period or frequency, Fishers’ Kappa test for white noise, Modeling > Time Series
• Sphere Packing—method of generating a Space Filling Design, (DOE), Space Filling Design
• sphericity test—univariate repeated measures test, uses Mauchley criterion, Fit Model Manova
• spinning plot—3-D spin of points, Spinning Plot
• spline fitting—specify stiffness parameter (lambda), Fit Y by X bivariate
• split column—reformats the layout of a JMP table, splits one or more columns into multiple columns based on the values of an ID variable
• split plot designs—generate design of experiments and analyze with Fit Model
• stack columns of a JMP data table, Stack command
• standard deviation—estimate and confidence interval for standard deviation in Distribution
• standard deviation tests equal to a given value; two-sided and one-sided Chi-square tests, Distribution
• standard error of the individual values—save as new data table column, Fit Y by X bivariate
• standard error of the mean—shows when appropriate
• standard error of the predicted values—save as new data table column, Fit Model SLS
• standard error of the residual values—save as new data table column, Fit Model SLS
• standard errors of estimates—wherever appropriate
• standard least squares options for parameter estimates—estimate, standard error of the estimate, t-ratio, significance p-value, 95% confidence limits, standardized beta and variance inflation factor (VIF)
• standardizing data—save standardized values as a new data table column, Distribution
• statistical quality control (SQC)—see control charts
• stem-and-leaf plot—Distribution
• step chart—step plot, connects points in time as steps Overlay Plot
• stepwise regression—all possible regressions, Fit Model Stepwise platform and Multivariate Methods > Discriminant
• straight-line regression—Fit Y by X bivariate
• Student’s t, t-test—one-way Anova (multiple comparison of all pairs of groups), Fit Y by X bivariate
• studentized residuals—compute then save as new data table column, Fit Model SLS
• subset a JMP data table—use Subset command or double-click histogram bars
• summary tables of statistics—for all analyses when appropriate, result of Group/Summary command
• supersaturated design in DOE—used when the number of runs is less than the number of terms in model, Custom Design
• Surface Plot—Graph menu platform that draws three-dimensional surfaces, rotates, has directional lighting, variable mesh, complete color selection, overlay four surfaces (iso surfaces, density surfaces keyboard shortcuts, residuals, background spinning), Surface Plot
• survival and reliability analysis— product limit (Kaplan-Meier) survival estimates, proportional hazards, (Cox model) regression, parametric survival models (for example exponential, extreme value, lognormal and Weibull estimation), competing causes analysis (see also recurrence analysis); Weibayes, Survival, Density and Hazard by Time plots, Failure Plots, Survival and Reliability > Survival/Reliability

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T

• t-test—1 sample to test Mean, 2 groups equal variance, 2 groups unequal variance, match paired, parameter estimates whenever appropriate, Distribution and Fit Y by X bivariate
• Tabulate —platform to present summary data in customized tabular form, has a drag and drop interface
• Taguchi design generation—DOE, Taguchi Design
• templates—data tables in the sample library stored with commonly needed formulas
• ternary plot—plots points or contours of a fourth variable against three independent variables, Ternary Plot
• tests for special causes (Western Electric Rules, Westgard rules)—quality control, Control Charts platform, Control Chart
• tests of independence—two-way contingency table analysis, Pearson and Likelihood Ratio Tests, Fit Y by X categorical
• three-dimensional spinning plot—look for clusters, patterns, and outliers, Spinning Plot
• time series modeling and forecasting—time series plots with forecasted values, residual plot, diagnostic charts, Differencing, ARIMA, Seasonal ARIMA, Smoothing Models (simple, double, linear, damped trend linear, and seasonal), and Winters Method, Modeling > Time Series
• tobit model—nonlinear regression with appropriate loss function (also see loss function templates), Modeling > Nonlinear
• tolerance intervals—one & two-sided, Distribution
• transpose—rows and columns interchanged in a JMP data table, optional By groups, Transpose command
• Tukey-Kramer test—multiple comparison of each pair of groups for one-way Anova, Fit Y by X oneway
• type 1 SS (sequential sum of squares)—general linear models, Fit Model, SLS

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U

• U control chart for attributes—quality control, Control Chart
• uncertainty—measured as total loglikelihood
• Uniform—method of generating a space filling design (DOE), Space Filling Design
• uniform precision—DOE, Response Surface Design
• uniformly weighted moving average chart—UWMA Control Charts
• univariate repeated measures—with sphericity test and degree of freedom adjustments (Greenhouse-Geisser and Huynh-Feldt), Fit Model Manova

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V

• V Mask—see cumulative sum plot, Control Chart
• Van der Waerden test— nonparametric test that k samples have equal means, Fit Y by X oneway
• variability analysis—variance component estimates, Gage R&R reports and plots, Variability/Gage Chart
• variance component estimates—random effects model specify one or more effects as random (see also mixed models), handles unbalanced designs, Fit Model SLS
• variance homogeneity—tests that the group variances are the same in a one-way ANOVA (see also Welch ANOVA, and O’Brien’s, Brown-Forsythe’s, Levene’s, and Bartlett’s test of homogeneity), Fit Y by X oneway
• varimax rotation—rotated components, Spinning Plot
• variogram—diagnostic for time series modeling, Modeling > Time Series

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W

• Wald Chi-square test—logistic regression, Fit Y by X logistic
• Weibull analysis—nonlinear regression with appropriate loss function, (see also loss function templates) Modeling > Nonlinear
• Weibull fitting—fits a Weibull 2- or 3- parameter Weibull distribution to data, Distribution
• Weibull survival curve—Survival and Reliability > Fit Parametric Survival
• Welch ANOVA— one-way ANOVA when there is non-homogeneity of variance, Fit Y by X oneway
• Western Electric Rules (tests for special causes)—quality control, Control Chart
• Westgard rules (tests for special causes)—quality control, Control Chart
• white noise tests—tests whether a time series is white noise, the Fisher-Kappa and BKS statistics are calculated for spectral density plots, Multivariate > Time Series
• Wilcoxon rank sum—two sample rank test equivalent to Mann-Whitney (see also Kruskal-Wallis for k samples), Fit Y by X oneway
• Wilcoxon signed-rank nonparametric test of mean, in matched pairs, tests the difference between two columns is zero, Distribution and Matched Pairs
• Wilcoxon test—survival analysis, Survival and Reliability > Survival/Reliability
• Wilk’s lambda—approximate F test for multivariate analysis of variance Fit Model Multivariate
• Winters method time series forecasting—(see time series modeling)

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Z

• z test—compare single Mean to a value, Distribution
• zone lines—zones for control charts, used with tests for special causes (see Western Electric Rules)
• zooming—use the magnifier glass tool to zoom in or out on any subset of a plot