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

Wendy Martin

提供方

隶属于 Master of Science in Data Science 学位
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Data Science Methods for Quality Improvement 专项课程科罗拉多大学波德分校

课程信息

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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.

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100% 在线

立即开始，按照自己的计划学习。

第 3 门课程（共 3 门）

Data Science Methods for Quality Improvement 专项课程

中级

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

完成时间大约为17 小时

英语（English）

对员工进行热门技能培训能否为您的公司带来益处？

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您将学到的内容有

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

您将获得的技能

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

可灵活调整截止日期

根据您的日程表重置截止日期。

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

第 3 门课程（共 3 门）

Data Science Methods for Quality Improvement 专项课程

中级

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

完成时间大约为17 小时

英语（English）

对员工进行热门技能培训能否为您的公司带来益处？

体验 Coursera 企业版

授课教师

Wendy Martin

W. Edwards Deming Professor of Management

Engineering Management Program

3,653 个学生

3 门课程

提供方

科罗拉多大学波德分校

立即开始攻读硕士学位

此课程隶属于科罗拉多大学波德分校提供的 100% 在线 Master of Science in Data Science。如果您被录取参加全部课程，您的课程将计入您的学位学习进程。

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了解顶级公司的员工如何掌握热门技能

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授课大纲 - 您将从这门课程中学到什么

周

周 1

完成时间为 2 小时

Correlation and Association

完成时间为 2 小时

9 个视频（总计 39 分钟）, 1 个阅读材料, 1 个测验

9 个视频

Introduction to Correlation and Association2分钟

The Coefficient of Correlation3分钟

Calculating the Coefficient of Correlation2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 Correlation4分钟

Measures of Association6分钟

Calculating Measures of Association5分钟

1 个阅读材料

Welcome and Where to Find Help10分钟

1 个练习

Correlation and Association1小时

周

周 2

完成时间为 5 小时

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.

完成时间为 5 小时

15 个视频（总计 76 分钟）

15 个视频

Introduction to the Analysis of Variance3分钟

ANOVA Principles4分钟

One Way ANOVA for Means5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 ANOVA4分钟

Statistical Importance5分钟

One Way ANOVA for Dispersion6分钟

Post Hoc Analysis - Tukey HSD5分钟

Post Hoc Analysis - Games and Howell4分钟

Roadmap for the One Way ANOVA6分钟

Roadmap for the One Way ANOVA7分钟

One Way ANOVA - Random Effects4分钟

One Way ANOVA - Random Effects5分钟

2 个练习

One Way ANOVA for Fixed Effects2小时

One Way ANOVA for Random Effects2小时

周

周 3

完成时间为 3 小时

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.

完成时间为 3 小时

11 个视频（总计 60 分钟）

11 个视频

Introduction to Continuous MSA4分钟

Measurement Systems Capability4分钟

Guidelines for Continuous MSA6分钟

Sources of Variation4分钟

Two Way Random Effects ANOVA4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 3分钟

1 个练习

Measurement Systems Analysis and Potential Studies1 小时 30 分

周

周 4

完成时间为 4 小时

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.

完成时间为 4 小时

7 个视频（总计 33 分钟）

关于 Data Science Methods for Quality Improvement 专项课程

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

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Measurement Systems Analysis

课程信息

您将学到的内容有

您将获得的技能