You have more data available than ever before, but are you tapping into it effectively using the best analytics? We'll help you discover new and improved ways to find trusted insights and learn to communicate them better, faster and easier. You'll also learn how Classification and Regression Trees (CART®) will expand your predictive analytics capabilities to better enable you to proactively make decisions. Join our Global Market Development Manager, Jenn Atlas, to review the additions to the latest release of Minitab Statistical Software. (60 min)
Join our Advisory User Experience Designer, Mindy Tomlinson. Searching for simple solutions to achieve the greatest impact with your work? Minitab Workspace enables you to move work forward with powerful visual tools, process maps, brainstorming diagrams and forms. All in one intuitive interface right at your finger tips. Our tools help form processes and identify opportunities ultimately making problems easier to solve. We are excited to share this new product with you and demonstrate how Minitab Workspace will lead you to discover better business opportunities! (45 min)
Join our Senior Data Scientist, Mikhail Golovnya. In this webinar we introduce a new exciting feature of Minitab -- Python integration module. We will explain how to setup the Python connector in a series of simple intuitive steps. Next, we will introduce the core elements of the new functionality: first, how to send Minitab data, such as individual constants and data columns, to the Python side; second, how to send the results of Python computing back to Minitab and conveniently report them in textual, graphical, and tabular forms. We will supply a set of simple Python scripts to illustrate all relevant activities. These scripts can serve as templates for further customizations and extensions. It will become clear that the new functionality is easily accessible to anyone and does not require prior experience with Python. In sum, the new Minitab/Python connector expands the capabilities of Minitab while preserving the conveniences of Minitab interface cherished by our long-term users. (60 min)
Join our Senior Advisory Statistician, Cheryl Pammer.
In this first of a 3-part series, we will move from using regression as an exploratory tool to using it as a powerful machine learning technique. Using real-world case studies, we will see how to mine observational data from your processes and extract valuable information. We will learn how and when to use specific model validation methods, including validation with a test set, leave-one-out validation and k-fold cross validation. By incorporating validation into model assessment, you will discover how to improve the accuracy of your predictive models. (60 min)
In this second of our 3-part series, we will transition to Binary Logistic Regression to predict outcomes with a categorical response variable or target. We will also venture further into modern-day predictive analytics by discussing various feature and model selection techniques. We will look beyond p-values for model reduction and discuss the benefits and disadvantages of several strategies for selecting high-performing predictive models.
In this final segment of our 3-part series, we will focus on classification and regression trees, or CART. There are many applications for CART, such as determining the conditions that lead to process defects, predicting the probability of a fraudulent transactions and determining the key drivers of anomalies in manufacturing processes. We will use examples to demonstrate how Classification and Regression Trees can provide an intuitive picture of complex relationships in your observational process data. (60 min)