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Minitab v17.3.1 Dual Edition



Minitab v17.3.1 Dual Edition | 338 MB



MINITAB Statistical Software is the ideal package for Six Sigma and other quality improvement projects. From Statistical Process Control to Design of Experiments, it offers you the methods you need to implement every phase of your quality project, along with features like StatGuide and ReportPad that help you understand and communicate your results. No package is more accurate, reliable, or easy to use. In addition to more statistical power than our previous release, MINITAB offers many exciting new features such as: A powerful new graphics engine that delivers engaging results that offer tremendous insight into your data An effortless method to create, edit, and update graphs The ability to customize your menus and toolbars so you can conveniently access the methods you use most.

Feature List

* New or Improved
Assistant
Measurement Systems Analysis *
Capability Analysis *
Graphical Analysis *
Hypothesis Tests *
Regression *
DOE *
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
Graphics

Easily create professional-looking graphics *
Scatterplots, matrix plots, boxplots, dotplots, histograms, charts, time series plots, etc.
Bubble plot *
Contour and rotating 3D plots
Probability and probability distribution plots
Edit attributes: axes, labels, reference lines, etc.
Interactively recreate custom graphs with new data
Easily place multiple graphs on one page
Automatically update graphs as data change
Brush graphs to explore points of interest
Export: TIF, JPEG, PNG, BMP, GIF, EMF
Regression

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

ANOVA *
General Linear Model *
MANOVA *
Multiple comparisons *
Response prediction and optimization *
Test for equal variances *
Plots: residual, factorial, contour, surface, etc. *
Analysis of means
Statistical Process Control

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 for multiple variables
Process Capability SixpackTM *
Tolerance intervals *
Acceptance sampling and OC curves
Measurement Systems Analysis

Data collection worksheets
Gage R&R Crossed: ANOVA and Xbar-R methods *
Gage R&R Nested
Gage R&R Expanded *
Misclassification probabilities
Gage run chart
Gage linearity and bias
Type 1 Gage Study
Attribute Gage Study - AIAG analytic method
Attribute agreement analysis

Design of Experiments

Two-level factorial designs *
Split-plot designs *
General factorial designs *
Plackett-Burman 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 *
Reliability/Survival

Parametric and nonparametric distribution analysis
Goodness-of-fit measures
ML and least squares estimates *
Exact failure, right-, left-, and interval-censored data
Accelerated life testing
Regression with life data
Reliability test plans
Threshold parameter distributions
Repairable systems
Multiple failure modes
Probit analysis
Weibayes analysis
Hypothesis tests on distribution parameters
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
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 and 2x2 crossover design *
Tables
Chi-square, Fisher's exact, and other tests *
Chi-square goodness-of-fit test
Tally individual variables
Simulations and Distributions

Random number generator
Density, cumulative distribution, and inverse cumulative distribution functions
Random sampling
Macros and Customization

Customizable menus and toolbars
Extensive preferences and user profiles.


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