- Accelerated life testing
- Acceptance sampling and OC curves
- Analysis of means
- Analysis of multiple failure modes
- Analysis of repairable systems
- Analyze variability for factorial designs
- Analyzing Tables of Counts
- ARIMA
- Attribute agreement analysis
- Attribute Gage Study – AIAG analytic method
- Attributes control charts: P, NP, C, U, P’, U’
- Auto-, partial auto-, and cross correlation functions
- Binary, ordinal and nominal logistic regression
- Binomial Distribution
- Botched runs
- Box-Cox transformation
- Calculating the Distribution Function
- Calculating the Inverse Distribution Function
- Capability Six-pack
- Cause-and-effect (fishbone) diagram
- Chi-Square Distribution
- Chi-square goodness-of-fit test
- Chi-square, Fisher’s exact, and other tests
- Cluster analysis
- Coding
- Column Statistics
- COM-enabled automation
- Comparing Two Samples
- Comprehensive command language
- Confidence and prediction intervals
- Converting Data Types
- Correlation and covariance
- Correlations
- Correspondence analysis
- Custom tests for special causes
- Customizable menus and toolbars
- Data collection worksheet generator
- Decomposition
- Density, cumulative distribution, and inverse cumulative distribution functions
- Discriminant analysis
- DMAIC Toolbar
- D-optimal and distance-based designs
- Easily create indicator variables
- Effects plots: normal, half-normal, Pareto
- Exact failure, right-, left-, and interval-censored data
- Exponential smoothing
- Extensive preferences and user profiles
- Factor analysis
- Friedman test
- Fully nested designs
- Gage linearity and bias
- Gage R&R Crossed: ANOVA and Xbar-R methods
- Gage R&R for more than two variables
- Gage R&R Nested
- Gage run chart
- General factorial designs
- General linear model (GLM)
- Goodness-of-fit measures
- Goodness-of-fit test for Poisson
- Historical/shift-in-process charts
- Hypothesis tests on distribution parameters
- Individual distribution identification
- Inference for a Single Proportion
- Inference for Two Proportions
- Item analysis and Cronbach’s alpha
- Johnson transformation
- Kruskal-Wallis test
- Linear regression
- Logistic Regression
- Macros and Execs
- Mann-Whitney test
- MANOVA
- Matrix Algebra in Minitab
- Misclassification probabilities
- Mixture designs
- ML and least squares estimates
- Mood’s median test
- Moving average
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- Multiple comparisons
- Multi-Vari chart
- Multivariate control charts: T-squared, generalized variance, MEWMA
- Nonlinear regression
- Normal Probability Plots
- Normality test
- NOVA
- One and two proportions
- One and two variances
- One- and two-sample Poisson rate tests
- One- and two-sample t
- One-sample Z
- One-Way ANOVA
- Orthogonal regression
- Paired t
- Parametric and nonparametric distribution analysis
- Pareto chart
- Partial least squares (PLS)
- Plackett-Burman and general full factorial designs
- Plots: distribution, probability, hazard, survival
- Plots: residual, main effects, interaction, cube, contour, surface, wireframe
- Plotting Data in a Graph Window
- Power curves
- Powerful macro capability
- Principal components analysis
- Probit analysis
- Process capability for multiple variables
- Process capability: normal, non-normal, attribute, batch
- Random number generator
- Random sampling
- Rare event control charts: G, T
- Regression
- Reliability test plans
- Residual plots
- Residual, main effects, and interaction plots
- Response optimization
- Response prediction
- Response surface designs
- Row Statistics
- Runs test
- Sample size for estimation
- Scatter plots
- Sign test
- Simple Regression Analysis
- Simulating Sampling Distributions
- Simulations for Confidence Intervals
- Simulations for Power Calculations
- Split-plot designs
- Stepwise and best subsets
- Student Distribution
- Symmetry plot
- Tabulating and Plotting
- Taguchi designs
- Tally and cross tabulation
- t-Confidence Intervals
- The Chi-square Test
- The Sign Test
- Threshold parameter distributions
- Time series plots
- Time-weighted control charts: MA, EWMA, CUSUM
- Tolerance intervals
- Transformations
- Trend analysis
- t-Tests
- Two-level factorial design
- Two-Way ANOVA
- Type 1 Gage Study (single part)
- Unbalanced nested designs
- User-specified designs
- Variables control charts: X-Bar, R, S, X-Bar-R, X-Bar-S, I, MR, I-MR, I-MR-R/S, zone, Z-MR
- Warranty analysis
- Weibayes analysis
- Wilcoxon Rank Sum Procedures
- Winters’ method
- z-Confidence Intervals
- z-Tests
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