Minitab Available on the Cloud

Minitab is now accessible Now from anywhere on the Cloud

  • Access from nearly any device
  • Available as both our desktop and new web app
  • Share projects with a single click
  • Access and store from Google DriveTM, Microsoft OneDrive® or local files
  • Single sign-on available

Improvements

Interface Improvement: Multi-Select in the Navigator

User Benefit

Selecting a range of output makes it easier for users who need to remove or send output from the Navigator.

Summary

One of the top feedback items from users, this improvement makes sending or removing multiple items from the navigator much easier.

Improved Model Selection for Classification and Regression Trees

User Benefit

Users can see the decision tree, model and node details in a single view, making alternative model selection easier than ever.

Summary

When users choose to view an alternative tree, a single view provides them with detailed information for all possible models.

Model Validation in Binary Logistic Regression and Poisson Regression

Variability Chart

User Benefit

Validation is the process of evaluating a trained model on a test data set. This feature makes it easier for users to create useful models.

Summary

Validation prevents model overfitting, which is an important aspect in machine learning. This feature is now available in the Predictive Analytics menu and within Stat-Regression, Stat-Binary Logistic Regression and Stat-Poisson Regression.

Visualizations

Variability Chart

1. The ability to specify multiple response variables for a given set of factors – this results in multiple graphs, one for each response.
2. The ability to brush individual observations.

User Benefit

It is easy to create multiple variability charts with a single click. Also, exploring data is easier with the added ability to brush individual observations.

Summary

The Variability chart dialog can now support multiple responses, and brushing points is available when interacting with the graph.

New Visualizations

Parallel Coordinates Plot

User Benefit

Parallel plots represent high dimensional data as a two-dimensional visualization. Data is represented in the form of a line making it easy to visualize trends.

Summary

The parallel coordinates plot is an efficient way to visualize multidimensional and multivariate data.

New Visualizations

Binned Scatterplot

User Benefit

Using a gradient to differentiate the density of data on a scatterplot makes it easier to communicate information to users. Users can also define the gradient as an average of another variable, providing additional flexibility for the visualization.

Summary

Binned scatterplots create meaningful graphics when displaying information for large data sets.

New Visualizations

Heat Map

User Benefit

Heat maps identify areas of interest. They can quickly uncover scenarios that lead to a high or low values.

Summary

Heatmaps are located in the Graph menu, between the bar and pie Charts. When you have a large number of factor levels, they may be easier than a bar chart to communicate areas that are different.