* New or Improved

**Assistant**

Measurement systems analysis

Capability analysis

Graphical analysis

Hypothesis tests

Regression

DOE

Control charts

**Healthcare Module**

**Graphics**

Graph Builder *

Binned scatterplots, boxplots, bubble plots, bar charts, correlograms, dotplots, heatmaps, histograms, matrix plots, parallel plots, scatterplots, time series plots, etc.

Contour and rotating 3D plots

Probability and probability distribution plots

Automatically update graphs as data change

Brush graphs to explore points of interest

Export: TIF, JPEG, PNG, BMP, GIF, EMF

**Basic Statistics**

Descriptive statistics

One-sample Z-test, one- and two-sample t-tests, paired t-test

One and two proportions tests

One- and two-sample Poisson rate tests

One and two variances tests

Correlation and covariance

Normality test

Outlier test

Poisson goodness-of-fit test

**Regression**

Cox regression *

Linear regression

Nonlinear regression

Binary, ordinal and nominal logistic regression

Stability studies

Partial least squares

Orthogonal regression

Poisson regression

Plots: residual, factorial, contour, surface, etc.

Stepwise: p-value, AICc, and BIC selection criterion

Best subsets

Response prediction and optimization

Model validation

**Analysis of Variance**

ANOVA

General linear models

Mixed models

MANOVA

Multiple comparisons

Response prediction and optimization

Test for equal variances

Plots: residual, factorial, contour, surface, etc.

Analysis of means

**Measurement Systems Analysis**

Data collection worksheets

Gage R&R Crossed

Gage R&R Nested

Gage R&R Expanded

Gage run chart

Gage linearity and bias

Type 1 Gage Study

Attribute Gage Study

Attribute agreement analysis

**Quality Tools**

Run chart

Pareto chart

Cause-and-effect diagram

Variables control charts: XBar, R, S, XBar-R, XBar-S, I, MR, I-MR, I-MR-R/S, zone, Z-MR

Attributes control charts: P, NP, C, U, Laney P’ and U’

Time-weighted control charts: MA, EWMA, CUSUM

Multivariate control charts: T2, generalized variance, MEWMA

Rare events charts: G and T

Historical/shift-in-process charts

Box-Cox and Johnson transformations

Individual distribution identification

Process capability: normal, non-normal, attribute, batch

Process Capability Sixpack^{TM}

Tolerance intervals

Acceptance sampling and OC curves

Multi-Vari chart

Variability chart

**Design of Experiments**

Definitive screening designs

Plackett-Burman designs

Two-level factorial designs

Split-plot designs

General factorial designs

Response surface designs

Mixture designs

D-optimal and distance-based designs

Taguchi designs

User-specified designs

Analyze binary responses

Analyze variability for factorial designs

Botched runs

Effects plots: normal, half-normal, Pareto

Response prediction and optimization

Plots: residual, main effects, interaction, cube, contour, surface, wireframe

**Reliability/Survival**

Parametric and nonparametric distribution analysis

Goodness-of-fit measures

Exact failure, right-, left-, and interval-censored data

Accelerated life testing

Regression with life data

Test plans

Threshold parameter distributions

Repairable systems

Multiple failure modes

Probit analysis

Weibayes analysis

Plots: distribution, probability, hazard, survival

Warranty analysis

**Power and Sample Size**

Sample size for estimation

Sample size for tolerance intervals

One-sample Z, one- and two-sample t

Paired t

One and two proportions

One- and two-sample Poisson rates

One and two variances

Equivalence tests

One-Way ANOVA

Two-level, Plackett-Burman and general full factorial designs

Power curves

**Predictive Analytics**

Automated Machine Learning *

CART® Classification

CART® Regression

Random Forests® Classification

Random Forests® Regression

TreeNet® Classification

TreeNet® Regression

**Multivariate**

Principal components analysis

Factor analysis

Discriminant analysis

Cluster analysis

Correspondence analysis

Item analysis and Cronbach’s alpha

**Time Series and Forecasting**

Time series plots

Trend analysis

Decomposition

Moving average

Exponential smoothing

Winters’ method

Auto-, partial auto-, and cross correlation functions

ARIMA

**Nonparametrics**

Sign test

Wilcoxon test

Mann-Whitney test

Kruskal-Wallis test

Mood’s median test

Friedman test

Runs test

**Equivalence Tests**

One- and two-sample, paired

2x2 crossover design

**Tables**

Chi-square, Fisher’s exact, and other tests

Chi-square goodness-of-fit test

Tally and cross tabulation

**Simulations and Distributions**

Random number generator

Probability density, cumulative distribution, and inverse cumulative distribution functions

Random sampling

Bootstrapping and randomization tests

**Macros and Customization**

Customizable menus and toolbars

Extensive preferences and user profiles

Powerful scripting capabilities

Python integration

R integration