This course is part of the Data Science Methods for Quality Improvement Specialization

Wendy Martin

Offered By

Part of the Master of Science in Data Science degree
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Data Science Methods for Quality Improvement SpecializationUniversity of Colorado Boulder

About this Course

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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.
This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

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Course 3 of 3 in the

Data Science Methods for Quality Improvement Specialization

Intermediate Level

Background knowledge in statistics is helpful; visit the Data Science Methods for Quality Improvement specialization as prerequisites to this course.

Approx. 16 hours to complete

English

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What 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

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 3 of 3 in the

Data Science Methods for Quality Improvement Specialization

Intermediate Level

Background knowledge in statistics is helpful; visit the Data Science Methods for Quality Improvement specialization as prerequisites to this course.

Approx. 16 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Wendy Martin

W. Edwards Deming Professor of Management

Engineering Management Program

3,864 Learners

4 Courses

Offered by

University of Colorado Boulder

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Data Science from University of Colorado Boulder. If you are admitted to the full program, your courses count towards your degree learning.

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Syllabus - What you will learn from this course

Week1

Week 1

2 hours to complete

Correlation and Association

2 hours to complete

9 videos (Total 39 min), 1 reading, 1 quiz

9 videos

Introduction to Correlation and Association2mThe Coefficient of Correlation3mCalculating the Coefficient of Correlation2mThe One Sample t Test for Correlation 6mFisher’s Z Test for Correlation4mSpearman’s Rank-Order Correlation4mThe Point Biserial Correlation4mMeasures of Association6mCalculating Measures of Association5m

1 reading

Welcome and Where to Find Help 10m

1 practice exercise

Correlation and Association1h

Week2

Week 2

5 hours to complete

The One Way Analysis of Variance (ANOVA) for Fixed and Random Effects

In this module, we will perform an Analysis of Variance for Fixed and Random Effects for a single factor and interpret results. We will first examine within versus between-group variation, and interpret the ANOVA source table. We will learn how to perform the ANOVA with Fixed Effects for means and dispersion, considering normality and equal/unequal variance. We'll create data visualizations of results, calculate statistical importance and perform post hoc analysis. Finally, we'll perform the ANOVA with Random Effects.

5 hours to complete

15 videos (Total 76 min)

15 videos

Introduction to the Analysis of Variance3mANOVA Principles4mOne Way ANOVA for Means5mThe ANOVA Source Table5mPerform an ANOVA in RStudio4mWelch's ANOVA for Unequal Variance2mData Visualization for ANOVA4mStatistical Importance5mOne Way ANOVA for Dispersion6mPost Hoc Analysis - Tukey HSD5mPost Hoc Analysis - Games and Howell4mRoadmap for the One Way ANOVA6mRoadmap for the One Way ANOVA7mOne Way ANOVA - Random Effects4mOne Way ANOVA - Random Effects5m

2 practice exercises

One Way ANOVA for Fixed Effects2hOne Way ANOVA for Random Effects2h

Week3

Week 3

3 hours to complete

Introduction to Measurement Systems Analysis for Continuous Data, Potential Studies for Continuous Data

In this module, we will understand the terms and concepts associated with measurement systems analysis and analyze measurement error to determine the potential capability of a measurement system. We will explore the guidelines for measurement systems analyses and the equations for measurement error and capability. We will then calculate the sources of variation from the ANOVA determine the largest sources of variation, and determine capability in comparison to both process variation and specification tolerance. Finally, we'll create data visualizations, and interpret the results of the analysis.

3 hours to complete

11 videos (Total 60 min)

11 videos

Introduction to Continuous MSA4mMeasurement Systems Capability4mGuidelines for Continuous MSA6mSources of Variation4mTwo Way Random Effects ANOVA4mEstimating Variance from Mean Squares5mThe Components of Variance 7mStudy Variation and Discrimination6mData Visualizations7mData Visualizations5mInterpreting Results 3m

1 practice exercise

Measurement Systems Analysis and Potential Studies1h 30m

Week4

Week 4

4 hours to complete

Short Term and Long Term Studies for Continuous Data

In this module, we will analyze measurement error to determine the short and long-term capability of a measurement system. We will build on what we have learned in the previous module, adding the evaluation of the underlying assumptions of normality, independence of part size/magnitude and measurement error, and stability of measurement error. We'll perform an ANOVA to determine sources of variation along with the determination of gauge discrimination. Finally, we'll create data visualizations, and interpret the results of the analysis.

4 hours to complete

7 videos (Total 33 min)

About the Data Science Methods for Quality Improvement Specialization

Data analysis skills are widely sought by employers, both nationally and internationally. This specialization is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability.

By completing this specialization, you will improve your ability to analyze data and interpret results as well as gain new skills, such as using RStudio and RMarkdown. Whether you are looking for a job in data analytics, operations, or just want to be able to do more with data, this specialization is a great way to get started in the field. Learners are encouraged to complete this specialization in the order the courses are presented. This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Data Science Methods for Quality Improvement

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Measurement Systems Analysis

About this Course

What you will learn

Skills you will gain