Data Analytics for Lean Six Sigma
Master data analytics techniques for Lean Six Sigma projects. Learn statistical tools and Minitab software to analyze and interpret project data.
Master data analytics techniques for Lean Six Sigma projects. Learn statistical tools and Minitab software to analyze and interpret project data.
This comprehensive course teaches data analytics techniques essential for Lean Six Sigma improvement projects. Led by Dr. Inez Zwetsloot, students learn to analyze and interpret project data using Minitab software. The course covers visualization techniques, probability distributions, statistical testing, and data-driven decision-making. While focused on Lean Six Sigma applications, the analytical tools taught are widely applicable across various business contexts. The practical approach emphasizes tool usage and result interpretation rather than mathematical theory.
4.8
(3,309 ratings)
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English
English (Original), Deutsch (Auto), हिन्दी (ऑटो), 19 more
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What you'll learn
Analyze and interpret data within Lean Six Sigma improvement projects
Use Minitab software for data analysis and visualization
Apply appropriate statistical tests for different types of data
Create and interpret various data visualizations
Understand probability distributions and their applications
Conduct hypothesis testing and interpret results
Skills you'll gain
This course includes:
282 Minutes PreRecorded video
12 assignments
Access on Mobile, Desktop
FullTime access
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There are 7 modules in this course
This comprehensive course focuses on data analytics techniques essential for Lean Six Sigma improvement projects. The curriculum covers fundamental statistical concepts and their practical applications in business settings. Students learn to visualize data, work with probability distributions, and conduct various statistical tests using Minitab software. The course emphasizes practical implementation over theoretical foundations, making it accessible to beginners while providing valuable tools for process improvement and data-driven decision-making.
Data and Lean Six Sigma
Module 1 · 2 Hours to complete
Understanding and visualizing data
Module 2 · 2 Hours to complete
Using probability distributions
Module 3 · 1 Hours to complete
Introduction to testing
Module 4 · 43 Minutes to complete
Testing: numerical Y and categorical X
Module 5 · 1 Hours to complete
Testing: numerical Y and numerical Y
Module 6 · 1 Hours to complete
Testing: categorical Y
Module 7 · 1 Hours to complete
Fee Structure
Payment options
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Instructor
Industrial Statistics Expert and Lean Six Sigma Educator Advancing Process Monitoring Research
Inez Zwetsloot is an Associate Professor at the University of Amsterdam, combining academic research with practical business consulting in applied statistics and operations management. Since earning her PhD in industrial statistics in 2016, she has made significant contributions to statistical process monitoring and control chart methodologies. Her expertise extends to teaching Lean Six Sigma courses to both professionals and students in The Netherlands since 2012, bridging the gap between theoretical research and practical application. Her research focuses on business analytics, process monitoring, and the integration of data science with Lean Six Sigma methodologies, making her a valuable contributor to both academic and industrial fields.
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4.8 course rating
3,309 ratings
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