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Minitab 22.2.2023 Key Features:
Assistant:
- Measurement systems analysis
- Capability analysis
- Graphical analysis
- Hypothesis tests
- Regression
- DOE
- Control charts
Graphics:
- Binned scatterplots, boxplots, charts, correlograms, dot-plots, 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, EM
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 variance 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
- Validation for Regression and Binary Logistic Regression
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:
- The sample size for estimation
- The 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
Non-Parametric:
- 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
- 2×2 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
Minitab Product Key [2023]
CDSD3-345YH-GTF67-8IO6Y-CDSD2
489CD-JHGRT-56576-JHGRE-CDS33
DSD32-RER45-67IUJ-HGFRE-CDSD3
Minitab License Key [2023]
TSD53-3423G-CDSD3-KIOLE
GDSD3-KIYRD-CD467-CDS33
KIOD3-CDS33-TRSD2-DS323
What’s New in Minitab?
This update includes additional visualizations, integrations, and general improvements:
- New Correlogram
- R Integration
- Improvements to heatmaps, parallel plot, binned scatterplot, and Lag
How to Install and Activate?
- Extract the compressed file.
- Install the software.
- Enjoy!
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