Lynda - Six Sigma: Green Belt
Size: 526 MB | Duration: 1h 53m | Video: AVC (.mp4) 1280x720 30fps | Audio: AAC 48KHz 2ch
Genre: eLearning | Level: Intermediate | Language: English
Size: 526 MB | Duration: 1h 53m | Video: AVC (.mp4) 1280x720 30fps | Audio: AAC 48KHz 2ch
Genre: eLearning | Level: Intermediate | Language: English
Six Sigma is a customer-focused, data-driven methodology that is widely used to analyze and improve the performance of processes, products, and services. In this course, get the training you need to become a Six Sigma Green Belt. Green Belts participate in—or lead—Six Sigma projects on a part-time basis under the guidance of a Black Belt. Operational excellence expert, master Black Belt trainer, and professor Dr. Richard Chua explains how to use Six Sigma and its process, quality, and statistical tools as he prepares you to become a Six Sigma Green Belt. Dr. Richard Chua builds upon his Six Sigma Foundations and Learning Minitab courses, and covers an array of topics, including measurement system analysis, descriptive statistics, hypothesis testing, design of experiments, statistical process control, and more.
* Six Sigma and the organization
* Collecting the voice of the customer
* Project management basics
* Process maps
* Sampling in data collection
* Measurement system analysis
* Measuring performance using descriptive statistics
* Process performance measures
* Hypothesis testing
* Testing for means, variances, proportions, and independence
* Correlation and regression
* Using selection matrices
* Using failure modes and effects analysis
* Developing control plans
* Statistical process control
* Collecting the voice of the customer
* Project management basics
* Process maps
* Sampling in data collection
* Measurement system analysis
* Measuring performance using descriptive statistics
* Process performance measures
* Hypothesis testing
* Testing for means, variances, proportions, and independence
* Correlation and regression
* Using selection matrices
* Using failure modes and effects analysis
* Developing control plans
* Statistical process control
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