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MINITAB STATISTICAL SOFTWARE

Features

Minitab®

* 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

  • 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 SixpackTM
  • 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

  • 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
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