Minitab Statistical Software is the Best Predictive Analytics Software for Scientists and Engineers. Minitab is powerful statistical software everyone can use to solve their toughest business challenges. The best-in-class statistical platform you can access anywhere, anytime on the cloud. Harness the power of statistics. Data is everywhere, but are you truly taking advantage of yours? Minitab Statistical Software can look at current and past data to discover trends, find and predict patterns, uncover hidden relationships between variables, and create stunning visualizations to tackle even the most daunting challenges and opportunities. With powerful statistics, industry-leading data analytics, and dynamic visualizations on your side, the possibilities are endless. So, Minitab is a statistical software package designed that is widely used by businesses and academic institutions to analyze data and make informed decisions. Also, check out IBM SPSS Statistics Software.
Minitab Statistical Software Full Version Free Download Screenshots:
The software is easy to use and provides a wide range of statistical tools, making it an ideal choice for users with varying levels of statistical knowledge. One of the key features of Minitab is its user-friendly interface. The software is designed to be intuitive, with clear labels and easy-to-understand menus that allow users to navigate and analyze data quickly. Additionally, Minitab provides a range of tutorials and support materials to help users get started and make the most of the software. Another benefit of Minitab is its extensive range of statistical tools. The software includes various descriptive and inferential statistics and tools for quality control, process improvement, and experimental design. Users can easily generate histograms, scatterplots, box plots, and other visualizations to help them analyze and understand their data. Minitab also offers advanced data analysis tools, such as regression analysis, multivariate analysis, and time series analysis. These tools allow users to uncover relationships between variables, make predictions, and identify trends over time. One of the key advantages of Minitab is its ability to handle large data sets. The software can easily import data from various sources, including Excel, CSV files, and databases, and can handle data sets with thousands of rows and columns. Minitab is also highly customizable, allowing users to tailor the software to their needs. The software provides options for customizing the look and feel of the interface, as well as the ability to create custom analyses and macros. Overall, Minitab is an excellent statistical software package users. Its user-friendly interface, extensive range of statistical tools, and ability to handle large data sets make it an ideal choice for businesses and academic institutions. Whether you are a seasoned data analyst or new to statistical analysis, Minitab provides the tools and support to make informed decisions based on data. Regardless of statistical background, Minitab can empower all parts of an organization to predict better outcomes, design better products and improve processes to generate higher revenues and reduce costs. Only Minitab offers a unique, integrated approach by providing software and services that drive business excellence from anywhere, thanks to the cloud. Key statistical tests include t-tests, one and two proportions, normality, chi-square and equivalence tests. Access modern data analysis and further explore your data with our advanced analytics and open-source integration. Skillfully predict, compare alternatives and easily forecast your business using our revolutionary predictive analytics techniques. Use classical methods in Minitab Statistical Software, integrate with open-source languages R or Python, or boost your capabilities further with machine learning algorithms like Classification and Regression Trees (CART) or TreeNet and Random Forests, now available in Minitab’s Predictive Analytics Module. Seeing is believing. Visualizations can help communicate your findings and achievements through correlograms, binned scatterplots, bubble plots, boxplots, dot plots, histograms, heatmaps, parallel plots, time series plots and more. Graphs seamlessly update as data changes, and our cloud-enabled web app allows for secure analysis sharing with lightning speed. So, if you need this software for your Windows, follow the link below and download it.
The Feature of Minitab Statistical Software Full Version:
- 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, EMF - 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 - 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
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
How to download and install IBMMinitab Statistical Software into Windows:
- First, Download Minitab Statistical from the link below.
- First, you must download Minitab Software from the link.
- After downloading, please use Winrar to extract.
- Now, you have installed your Minitab Statistical software into Windows.
If you wish to download the Minitab Statistical program, share it with your friend and follow the direct downloader link.