Features List Minitab 18

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Measurement systems analysis *
Capability analysis
Graphical analysis
Hypothesis tests
Control charts  *

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

Analysis of Variance

General linear models *
Mixed models *
Multiple comparisons *
Response prediction and optimization *
Test for equal variances
Plots: residual, factorial, contour, surface, etc.
Analysis of means

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


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


Principal components analysis
Factor analysis
Discriminant analysis
Cluster analysis
Correspondence analysis
Item analysis and Cronbach’s alpha


Sign test
Wilcoxon test
Mann-Whitney test
Kruskal-Wallis test
Mood’s median test
Friedman test
Runs test


Chi-square, Fisher’s exact, and other tests
Chi-square goodness-of-fit test
Tally and cross tabulation

Macros and Customization

Customizable menus and toolbars
Extensive preferences and user profiles
Powerful scripting capabilities


Scatterplots, matrix plots, boxplots, dotplots, histograms, charts, 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


Linear and nonlinear regression
Binary, ordinal and nominal logistic regression *
Stability studies
Partial least squares
Orthogonal regression *
Poisson regression
Plots: residual, factorial, contour, surface, etc.
Stepwise and best subsets
Response prediction and optimization

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

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 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

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

Time Series and Forecasting

Time series plots
Trend analysis
Moving average
Exponential smoothing
Winters’ method
Auto-, partial auto-, and cross correlation functions

Equivalence Tests

One- and two-sample, paired
2×2 crossover design

Simulations and Distributions

Random number generator
Probability density, cumulative distribution, and inverse cumulative distribution functions
Random sampling