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.
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Spécialisation Data Science Methods for Quality ImprovementUniversité du Colorado à BoulderÀ propos de ce cours
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Dates limites flexibles
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Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 3 dans le
Niveau intermédiaire
Background knowledge in statistics is helpful; visit the Data Science Methods for Quality Improvement specialization as prerequisites to this course.
Approx. 17 heures pour terminer
Anglais
Sous-titres : Anglais
Ce que vous allez apprendre
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
Compétences que vous acquerrez
- 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
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 3 dans le
Niveau intermédiaire
Background knowledge in statistics is helpful; visit the Data Science Methods for Quality Improvement specialization as prerequisites to this course.
Approx. 17 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Université du Colorado à Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
Commencez à travailler pour obtenir votre master
Ce cours fait partie du diplôme intégralement en ligne Master of Science in Data Science de Université du Colorado à Boulder.
Si vous êtes admis(e) au programme complet, vos cours sont pris en compte dans votre apprentissage diplômant.
Programme de cours : ce que vous apprendrez dans ce cours
2 heures pour terminer
Correlation and Association
In this module, we will learn to identify, characterize and analyze relationships between two variables. We will first learn about correlation between two continuous variables and tests for significance. Next, we will learn about correlation for ordinal variables, and association for one nominal and one continuous variable. Finally, we will learn to assess relationship for two nominal variables.
2 heures pour terminer
9 vidéos (Total 39 min), 1 lecture, 1 quiz
5 heures pour terminer
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 heures pour terminer
15 vidéos (Total 76 min)
3 heures pour terminer
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 heures pour terminer
11 vidéos (Total 60 min)
4 heures pour terminer
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 heures pour terminer
7 vidéos (Total 33 min)
À propos du Spécialisation Data Science Methods for Quality Improvement
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.
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