In this course, you will learn to analyze measurement systems for process stability and capability and why having a stable measurement process is imperative prior to performing any statistical analysis. You will analyze continuous measurement systems and statistically characterize both accuracy and precision using R software. You will perform measurement systems analysis for potential, short-term and long-term statistical control and capability. Additionally, you will learn how to assess a discrete measurement and perform analyses for internal consistency, concordance between assessors, and concordance with a standard. Finally, you will learn how to make decisions on measurement systems process improvement.

About this Course
Background knowledge in statistics is helpful; visit the Data Science Methods for Quality Improvement specialization as prerequisites to this course.
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Try Coursera for BusinessWhat you will learn
Understand the terms and concepts associated with measurement systems analysis
Analyze measurement error to determine the potential capability of a measurement system
Analyze measurement error to determine the short-term and long-term capability of a measurement system
Analyze a measurement system for discrete data using potential, short-term, and long-term studies
Skills you will gain
- Analyze a continuous measurement system for sources of variation capability
- Analyze a discrete measurement system for validity and agreement
- Use RMarkdown to create a report
- Make decisions about measurement systems acceptability
Background knowledge in statistics is helpful; visit the Data Science Methods for Quality Improvement specialization as prerequisites to this course.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Start working towards your Master's degree
Syllabus - What you will learn from this course
Correlation and Association
The One Way Analysis of Variance (ANOVA) for Fixed and Random Effects
Introduction to Measurement Systems Analysis for Continuous Data, Potential Studies for Continuous Data
Short Term and Long Term Studies for Continuous Data
About the Data Science Methods for Quality Improvement Specialization

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