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Education & Seminars
Statistics for 6 Sigma
This course material has been recently updated!
This hands-on course focuses on the essential statistical tools for implementing your Six Sigma program! Whether you are a Novice or an Expert, you will learn how to use Excel spreadsheet statistical applications to your advantage!
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WHO SHOULD ATTEND
This course is intended for those involved in design, test, or analysis, who want a better understanding of advanced statistical concepts to use during design and testing a product.
The Statistics for Six Sigma course is based on the DMAIC (Design, Measure, Analyze, Improve, and Control) Model, and is applicable for improving quality across many industries including biotech, network computer providers, semiconductor, and even fiduciary applications. The course presents the DMAIC model in an easy to understand fashion with targeted examples of how specific statistical tools can be leveraged and applied to real world data. The course is a targeted training in that it directly shows the appropriate tools for different applications.
This Statistics for Six Sigma course presents a number of statistical tools to assist you in evaluating process variation and to make sound decisions based on your data. Specific statistical tools aligned with the DMAIC Six Sigma model include:
Process Mapping and Sub-process Mapping
Pareto Charts and Check sheets for Attribute and Visual Data
Descriptive Statistics and Central Limit Theorem (CLT)
Sample Size Determination
X Bar and R Control Charts, and Short Run SPC
Process Capability (Cp & Cpk) and Sample Size Determination
Yield Improvement techniques
Interpreting data, trend analysis, and
Basics of correlation techniques
Learning Objectives: Upon completion of this course, participants will be able to:
Construct Control Charts for attribute data.
Construct Ave. and Range control charts for variables data.
Construct 90% and 95% Confidence Intervals using the mean and standard deviation.
Distinguish between Process Control and Process Capability.
Perform a Correlation Studies and interpret results.