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Measurement Systems Analysis

Measurement Systems Analysis

本课程是 Data Science Methods for Quality Improvement 专项课程的一部分

位教师：Wendy Martin

1,839 人已注册

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5个模块

深入了解一个主题并学习基础知识。

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中级等级

推荐体验

灵活的计划

2 周在 10 小时一周

自行安排学习进度

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5个模块

深入了解一个主题并学习基础知识。

10 条评论

中级等级

推荐体验

灵活的计划

2 周在 10 小时一周

自行安排学习进度

攻读学位

了解更多

您将学到什么

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

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作业

7 项作业

授课语言：英语（English）

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Data Science Methods for Quality Improvement 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

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该课程共有5个模块

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://hua.dididi.sbs/degrees/master-of-science-data-science-boulder.

单元详情

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.

涵盖的内容

9个视频3篇阅读材料1个作业2个讨论话题

9个视频总计39分钟

Introduction to Correlation and Association2分钟
The Coefficient of Correlation3分钟
Calculating the Coefficient of Correlation3分钟
The One Sample t Test for Correlation 6分钟
Fisher’s Z Test for Correlation4分钟
Spearman’s Rank-Order Correlation4分钟
The Point Biserial Correlation5分钟
Measures of Association6分钟
Calculating Measures of Association5分钟

3篇阅读材料总计21分钟

Course Updates and Accessibility Support1分钟
Earn Academic Credit for your Work!10分钟
Course Support10分钟

1个作业总计60分钟

Correlation and Association60分钟

2个讨论话题总计20分钟

Introduce Yourself!10分钟
Correlation and Association10分钟

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.

涵盖的内容

15个视频2个作业1个讨论话题

15个视频总计76分钟

Introduction to the Analysis of Variance4分钟
ANOVA Principles4分钟
One Way ANOVA for Means6分钟
The ANOVA Source Table5分钟
Perform an ANOVA in RStudio4分钟
Welch's ANOVA for Unequal Variance2分钟
Data Visualization for ANOVA5分钟
Statistical Importance6分钟
One Way ANOVA for Dispersion6分钟
Post Hoc Analysis - Tukey HSD6分钟
Post Hoc Analysis - Games and Howell4分钟
Roadmap for the One Way ANOVA6分钟
Roadmap for the One Way ANOVA8分钟
One Way ANOVA - Random Effects5分钟
One Way ANOVA - Random Effects5分钟

2个作业总计240分钟

One Way ANOVA for Fixed Effects120分钟
One Way ANOVA for Random Effects120分钟

1个讨论话题总计10分钟

One Way ANOVA for Fixed and Random Effects10分钟

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.

涵盖的内容

11个视频1个作业1个讨论话题

11个视频总计60分钟

Introduction to Continuous MSA5分钟
Measurement Systems Capability4分钟
Guidelines for Continuous MSA6分钟
Sources of Variation5分钟
Two Way Random Effects ANOVA5分钟
Estimating Variance from Mean Squares5分钟
The Components of Variance 7分钟
Study Variation and Discrimination6分钟
Data Visualizations7分钟
Data Visualizations5分钟
Interpreting Results 4分钟

1个作业总计90分钟

Measurement Systems Analysis and Potential Studies90分钟

1个讨论话题总计10分钟

Measurement Systems Analysis and Potential Studies10分钟

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.

涵盖的内容

7个视频2个作业1个讨论话题

7个视频总计33分钟

Short Term Measurement Systems Analysis4分钟
Testing Assumptions, Evaluating Control6分钟
Measurement Error versus Part Size5分钟
Short Term Analysis5分钟
Long Term Measurement Systems Analysis4分钟
Evaluating Control5分钟
Measurement Error versus Part Size4分钟

2个作业总计180分钟

Short Term Measurement Systems Analysis90分钟
Long Term Measurement Systems Analysis90分钟

1个讨论话题总计10分钟

Short and Long Term Measurement Systems Analysis10分钟

In this module, we will analyze a discrete measurement system to determine agreement, consistency, and validity. We will first familiarize ourselves with the terms, definitions, and procedures associated with Discrete Measurement Systems Analysis. Next, we will explore the measurement of agreement using the Kappa statistic and the measure of disagreement using the test of symmetry. We will then learn to perform analyses for concordance with two appraisers and two categories, two appraisers more than two categories, and more than two appraisers. We will analyze appraisers for internal consistency. Finally, we'll assess validity (concordance with a standard).