University of Colorado Boulder
Stability and Capability in Quality Improvement
University of Colorado Boulder

Stability and Capability in Quality Improvement

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

Taught in English

Some content may not be translated

Wendy Martin

Instructor: Wendy Martin

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Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

9 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

What you'll learn

  • Understand how to use, select, and interpret process control charts to identify special causes of variation

  • Create and interpret control charts for normal and non-normal distributions

  • Create and interpret control charts for discrete data

  • Analyze the capability of a process to meet customer specifications

Details to know

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Assessments

5 quizzes

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

9 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Data Science Methods for Quality Improvement Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 5 modules in this course

In this module, you will learn how to define a process and break it down into components for the purpose of identifying potential sources of variation. You will learn how to classify variation into common and special causes through the use of a control chart. You’ll discover the Taguchi Loss function, and how it relates to the philosophy of quality, and its association to the product control and process control cycles. You will learn the basic anatomy of a control chart as well as the process used to create a control chart, and common errors encountered when using a control chart in practice. You will be able to calculate an appropriate sample size, as well as determine when a process is in control or out of control based on statistical rules.

What's included

13 videos2 readings1 quiz2 discussion prompts

In this module, you will learn how to select the appropriate chart given information on sample size and data type. You’ll learn how to create and interpret control charts with subgroups for variables data, as well as how to create them in R. You will also create and interpret control charts with a sample size of one data that is normally distributed. You'll learn how to monitor other statistics using the Individuals and Moving Range Chart. Finally, you will interpret the control charts for statistical control / stability.

What's included

11 videos1 quiz1 discussion prompt

In this module, you will learn how to create an X and Moving Range Chart when the underlying distribution is not normally distributed. You’ll learn how to calculate control limits for the X and MR Charts with LogNormal transformed distribution and exponential distribution. Additionally, you will learn how to fit a distribution to the data and calculate control limits associated with the selected distribution. Finally, you will interpret the control charts for statistical control / stability.

What's included

12 videos1 quiz1 discussion prompt

In this module, you will learn how to compare process variation to customer specifications. You’ll learn the three indices associated with capability measures and the three indices associated with performance measures. Additionally, you will learn to assess capability and performance when the data are not normally distributed.

What's included

16 videos1 quiz1 discussion prompt

In this module, you will learn how to create and analyze control charts for discrete data. You will learn how to differentiate between data that are Binomial and data that are Poisson distributed in order to select the appropriate control chart. Additionally, you will learn to assess capability using an appropriate discrete probability model.

What's included

12 videos1 quiz1 discussion prompt

Instructor

Instructor ratings
4.2 (5 ratings)
Wendy Martin
University of Colorado Boulder
6 Courses6,200 learners

Offered by

Recommended if you're interested in Probability and Statistics

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