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Alphabetical List of Features

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

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

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

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

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