# Minitab Assignment Help

## Minitab Assignment Help

In recent times, the application of Minitab in statistics has become widespread especially in the area of Descriptive Statistics, Regression Analysis, Testing of Hypothesis and Control Charts etc. Our Statistics tutors being proficient in these multiple areas can provide you the quality and timely solutions in the form of Statistics using Minitab homework help, assignment help, term paper help and exam preparation help. Our assignment/homework help tutors hold PhD degrees or Masters and are well versed with any referencing style, be it Harvard or APA or any other. Our experts are available 24×7 to help high school/ college/ university students with their assignments. Along with College Statistics Homework Help and University Statistics Homework Help we also provide Online Statistics using Minitab tutoring for high school, undergraduate, graduate and PhD level students

Following is the list of comprehensive topics in which we offer the quality solutions:

• 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
• Correspondence analysis
• Correlations
• Custom tests for special causes
• 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
• 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
• The 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-Test