About Minitab
Minitab is available for free download from our software library. Predict, visualize, analyze, and harness the power of your data to tackle the toughest challenges and prevent errors before they occur. Data is everywhere these days, but are you truly leveraging yours? Minitab Statistical Software can examine both current and past data to identify trends, forecast patterns, uncover hidden relationships between variables, visualize data interactions, and pinpoint key factors to answer even the most complex questions. Visuals are great, but pair them with analytics to make them exceptional. With the power of statistics and data analysis on your side, the possibilities are endless.
Features of Minitab Full Download
Discover
Regardless of statistical background, Minitab empowers all parts of an organization to predict better outcomes, design superior products, and enhance processes to generate higher revenue and reduce costs. Minitab offers a unique, integrated approach by providing software and services that drive business excellence from anywhere, thanks to the cloud. Statistical tests include t-tests, one and two proportions, normality tests, chi-square tests, and equivalence tests.
Predict
Access modern data analysis and explore your data further with our advanced analytics and open-source integration. Skillfully anticipate alternatives, compare them, and forecast your business with ease using our revolutionary predictive analytics techniques. Use classic methods in Minitab Statistical Software, integrate with open-source languages like R or Python, or enhance your capabilities further with machine learning algorithms such as Classification and Regression Trees (CART®), TreeNet®, and Random Forests®, now available in Minitab's Predictive Analytics module.
Achieve
Seeing is believing. Visualizations can help communicate your results and achievements through graphs, visual scatterplots, bubble charts, box plots, dot plots, histograms, heat maps, parallel plots, time series plots, and more. Charts update seamlessly as data changes, and our cloud-supported web app allows for lightning-fast, secure analysis sharing.
Assistant
- Measurement System Analysis
- Capability Analysis
- Graphical Analysis
- Hypothesis Tests
- Regression
- DOE
- Control Charts
Graphics
- Flexible scatterplots*, box plots, charts, illustration charts*, dot plots, heat maps*, histograms, matrix plots, parallel plots*, scatterplots, time series plots, etc.
- 3D contour and rotating plots
- Probability and probability distribution plots
- Automatically update graphs as data changes
- Brushed graphs for exploring points of interest
- Export: TIF, JPEG, PNG, BMP, GIF, EMF
Basic Statistics
- Descriptive statistics
- One-sample Z-test, one-sample and two-sample t-tests, paired t-test
- One and two proportions tests
- One-sample 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, factor, contour, surface, etc.
- Step-by-step: p-value, AICc, and BIC selection criteria
- Best subsets
- Predict and optimize responses
- Validate regression and binary logistic regression*
Analysis of Variance
- ANOVA
- General linear models
- Mixed models
- MANOVA
- Multiple comparisons
- Predict and optimize responses
- Test for equal variances
- Plots: residual, factors, contour, surface, etc.
- Means analysis
Measurement System 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
- Variable control charts: XBar, R, S, XBar-R, XBar-S, I, MR, I-MR, I-MR-R/S, Zone, Z-MR
- Attribute 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 event charts: G, T
- Historical/process shift 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
- Multivariate chart
- Variance 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
- Binary response analysis
- ANOVA for factorial designs
- Failed runs
- Effects plots: normal, half-normal, Pareto
- Predict and optimize responses
- Plots: residual, main effects, interaction, cube, contour, surface, wireframe
Reliability/Survival
- Parametric and nonparametric distribution analysis
- Goodness-of-fit measures
- Complete failure, right-, left-, and interval-censored data
- Accelerated life testing
- Regression with life data
- Test plans
- Threshold parameter distributions
- Repairable systems
- Multiple failure modes
- Probability 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-sample and two-sample t-tests
- One and two proportions
- One-sample and two-sample Poisson rates
- One and two variance tests
- Equivalence tests
- One-way ANOVA
- Two-level, Plackett-Burman, and full factorial designs
- Power curves
Predictive Analytics *
- CART® Classification
- CART® Regression
- Random Forests® Classification*
- Random Forests® Regression*
- TreeNet® Classification*
- TreeNet® Regression*
Multivariate
- Principal component 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
- Autocorrelation, partial, and cross-correlation functions
- ARIMA
Nonparametrics
- Sign test
- Wilcoxon test
- Mann-Whitney test
- Kruskal-Wallis test
- Median test
- Friedman test
- Runs test
Equivalence Tests
- One-sample and two-sample, paired
- 2x2 crossover design
Tables
- Chi-square and Fisher's exact tests and other tests
- Chi-square goodness-of-fit test
- Cross-tabulation and 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
- Global preferences and user profiles
- Robust scripting capabilities
- Python integration
- R integration
System Requirements
- Operating System: Windows 10 and newer (64-bit)
- RAM: 64-bit systems: 4 GB or more recommended
- Processor: Intel® Pentium® 4 or AMD Athlon™ Dual Core, with SSE2 technology
- Hard Disk Space: 2 GB (minimum) of available free space
- Screen Resolution: 1024 x 768 or higher
- Browser: A web browser is required for Minitab Help.
Supported Languages
Chinese, English, French, German, Japanese, Korean, Portuguese, Spanish
Unzip Password: 123
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