Minitab features and reviews of 2020

Minitab statistical analysis software helps data analysts and scientists to monitor trends, analyze and visualize data, gain valuable insights, and solve business problems.

Overview

Minitab is a statistical and data visualization software for data analysts, data scientists, and businesses of all sizes. Minitab statistical analysis software has use cases in industries such as apparel, automotive, banking and insurance, chemicals, food and beverage, medical, pharmaceuticals, nonprofit, manufacturing, professional services, and the government.

Companies use Minitab statistical analysis software to monitor trends, predict patterns, and future outcomes. With this software, data scientists can identify interactions and relationships between variables, gain insights to solve problems and answer critical business questions.

The software provides a complete set of statistical and data visualization features to help organizations make data-driven decisions that lead to successful business outcomes. With Minitab statistical analysis software, data scientists can explore and analyze data using basic statistical models such as descriptive statistics, correlation, covariance, normality, and outlier testing.

The tool lets business analysts perform statistical analyses such as correlations, mathematical modeling, time series, multivariate methods, and chi-square test for association. Engineering teams can analyze and optimize product, system, and equipment reliability using statistical methods such as test plans, distribution analysis, warranty analysis, repairable systems analysis, probit analysis, and regression with life data.

Minitab statistical analysis software allows users to analyze data, make accurate predictions and business forecasts. The software supports predictive analytics, including factor analysis, logistic regression, cluster variables, and Classification and Regression Trees (CART).

Data scientists and engineers use Minitab statistical analysis software to build and validate data and analytical models faster. With model validation, users can quickly assess the accuracy of regression models, partition, or resample their data into test and training sets.

Minitab statistical analysis software supports third-party integrations with data analysis tools such as Python. Data scientists can explore possibilities and extend analytical capabilities directly from the interface or using a macro. With this software, users can collaborate with other data scientists to get more out of their data and solve even more problems.

Product Details 

Minitab statistical analysis software offers an extensive set of data analysis and visualization tools to help organizations make informed decisions, drive operational excellence, and achieve better business outcomes.

This software supports basic statistical models such as descriptive statistics, correlation, and covariance, normality, and outlier test, paired t-test, one-sample z-test, one and two-sample t-tests, one and two-sample Poisson rate tests, one and two proportions tests, one and two variances tests, Poisson goodness-of-fit test.

With this tool, businesses can control, manage, and improve quality using statistical methods such as measurement system analysis, control charts, capability analysis, acceptance sampling, and tolerance intervals.

Managers and engineers can use this tool to achieve equipment or product reliability, eliminate equipment downtime, and save time. They can perform statistical analysis to understand the pattern and failure modes of products, parts, and systems. This software supports statistical analysis for Reliability Engineering such as distribution analysis, test plans, warranty analysis, repairable systems analysis, regression with life data, and probit analysis.

Minitab statistical analysis software helps product development teams make critical decisions during product and process development. Users can carry out statistical analysis, including power and sample size tests, and Design of Experiments (DOE).

Companies use this tool for process design, process qualification, and process validation. This software lets users analyze and visualize using methods such as Analysis of Variance (ANOVA), regression, hypothesis testing, measurement systems analysis, process capability, control charts, capability analysis, tolerance intervals, and acceptance sampling.

Minitab statistical analysis software allows businesses to analyze data, make predictions, and forecast business outcomes using predictive analytics and machine learning techniques. With this tool, managers can mine customer data and predict future trends such as market demands, buying behavior, using analytics models including cluster variables, factor analysis, logistic regression, Classification, and Regression Trees (CART’)

With this robust predictive analytics toolkit, managers and companies can expand their decision-making capabilities, avoid bottlenecks and operations downtimes, save costs, and proactively optimize business processes to achieve better results.

Data scientists and engineers use Minitab statistical analysis software to build and validate data and analytical models faster. With model validation, users can quickly assess the accuracy of regression models, effortlessly partition or resample their data into test and training sets speedily.

This software supports statistical models such as regression, linear and nonlinear regression, binary, ordinal, and nominal logistic regression. Data analysts and companies can synthesize enormous amounts of data, evaluate their forecast accuracy, and gain valuable insights with more accelerated performance.

Organizations and data analysts use Minitab statistical analysis software to visualize and represent data in an effective way. Graphs and charts make it easy for managers, professionals, and businesses to present and interpret large datasets.

With this software, businesses can demonstrate patterns, trends, and relationships between multiple sets of data. Minitab statistical analysis software supports multiple graphs and chart types, including histograms, scatterplots, box plots, matrix plots, dot plots, charts, time series plots, contour and rotating 3D plots, probability, and probability distribution plots.

The software automatically update graphs when there is corresponding data change. Users can brush graphs to explore critical data points of interest and identify worksheet information. Also, users can export graphs in multiple file-formats, including EMF, TIF, JPEG, PNG, GIF, and BMP.

Minitab statistical analysis software helps data analysts and managers get more out of their data. Minitab offers an assist tool that guides users through their data analysis, interpretation, results, and presentation. The tool helps managers pick the appropriate statistical tool by asking a series of questions to know the objective of the analysis and data type.

Minitab Assistant offers clear guidelines to help users collect data, enter data, and analyze data quickly. With this tool, data managers can interpret results with confidence. The tool provides reports to help users understand their data analysis.

With the summary reports, users can understand data trends and answer relevant questions. The diagnostic reports provide additional details to help managers gain more in-depth insight into their data. Report cards help users verify their data analysis. It provides assumption checks and identifies concerns such as normality and sample size issues, or unusual data points.

Minitab statistical analysis software supports third-party integrations with data analysis tools such as Python. Data scientists can extend analytical capabilities directly from the interface or using a macro. With this software, users can collaborate with other data scientists to get more out of their data and solve problems faster.

Recap

Minitab statistical analysis software helps business and data analyst perform basic and advanced statistical analysis. With this tool, users can visualize data, monitor trends, and generate more in-depth insights. Companies use this tool to make accurate predictions and informed decisions that will drive business performance.