Tips & Tricks for CART Classification and Regression Trees in Minitab
Now, more than ever, we understand that healthcare professionals are under pressure to calculate, analyze, and improve key process indicators (KPIs) around critical outcomes such as wait time, patient safety, and re-admission. This level of data analysis may not come naturally to those without a background in statistics, and that's where Minitab's Healthcare Module comes in to help.
Watch on-demand to hear from Minitab's Senior Analytics Consultant, Ming Dong, who will showcase our purpose-built module that will help healthcare professionals with direct prompts, guidance, and support pages, all in healthcare-friendly terminology.
During this session, you will:
- Learn how to visualize, analyze, and predict patient wait times using graphical tools in Minitab
- Discover how to demonstrate results following a process improvement project and monitor ongoing patient safety
- Understand re-admission data using predictive analytics and Classification & Regression Trees (CART®)
- Explore more valuable visualizations using Minitab's Graph Builder, using real-life health data
Further resources:
- Talk to Minitab about how the Healthcare Module can help you tackle your improvement challenges.
- Learn more about Minitab's solutions for the Healthcare Industry.
- Visit our Webinars page to see what's coming up and watch past webinars on-demand.
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About the Presenter
Ming Dong
Senior Analytics Consultant/Technical Training Specialist, Minitab
"My goal is to make my courses practical and relevant for professionals from all types of businesses."
Ming Dong is one of only a handful of practitioners across the Asia Pacific Region to be a certified trainer for Minitab’s flagship product, Minitab Statistical Software. The training certification process is the culmination of years of statistical training with real-life application of data analysis in the industry.
Ming’s formal qualifications include an undergraduate degree in Industrial Engineering Management, a Masters of Computer Science from the University of New South Wales, and a Masters of Applied Statistics from Macquarie University. Ming has a unique and profound understanding of the application of statistics in the business world.
In addition, Ming has broad business development experience, developed through his work in senior technical roles for large organizations such as Toshiba, OzEmail, and National Computing Systems Singapore. As a university research officer at Macquarie University, he had several papers published in the field of Bioinformatics.
His extensive business development and industry experience are the reason why Ming has been engaged by some of the world’s largest mining, banking, and medical devices companies to provide consulting services in the application of data analysis.