- Data Science
- Process Engineering
- Data Analysis
- Quality Improvement
- Rstudio
- analyzing data
- describing data
- using R
- graphing data
- Make decisions about process improvement
- Analyzing a process for stability
- Analyzing a process for capability
Data Science Methods for Quality Improvement Specialization
Launch your career in data science.. Master strategies in data science methods for quality improvement.
Offered By
What you will learn
Manage, describe, and analyze data using applied statistics
Apply continuous and/or discrete data methods for process analysis, improvement, and ongoing management in a business or workplace
Analyze measurement systems to ensure their stability and capability
Calculate descriptive statistics and create graphical representations using R software
Skills you will gain
About this Specialization
Applied Learning Project
Learners develop an understanding of how to manage, describe, and analyze continuous and discrete data using examples from business and industry. They explore how to assess processes for sources of variation through time as well as determine process capability with respect to customer requirements. Learners gain familiarity with the analysis procedures to assess measurement systems for continuous and discrete data in order to make decisions regarding the capability and acceptability of the measurement system. Assignments require learners to perform analyses for various data types and scenarios, interpret results, and make appropriate decisions.
Familiarity with RStudio and applied statistics is recommended.
Familiarity with RStudio and applied statistics is recommended.
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

There are 3 Courses in this Specialization
Managing, Describing, and Analyzing Data
In this course, you will learn the basics of understanding the data you have and why correctly classifying data is the first step to making correct decisions. You will describe data both graphically and numerically using descriptive statistics and R software. You will learn four probability distributions commonly used in the analysis of data. You will analyze data sets using the appropriate probability distribution. Finally, you will learn the basics of sampling error, sampling distributions, and errors in decision-making.
Stability and Capability in Quality Improvement
In this course, you will learn to analyze data in terms of process stability and statistical control and why having a stable process is imperative prior to perform statistical hypothesis testing. You will create statistical process control charts for both continuous and discrete data using R software. You will analyze data sets for statistical control using control rules based on probability. Additionally, you will learn how to assess a process with respect to how capable it is of meeting specifications, either internal or external, and make decisions about process improvement.
Measurement Systems Analysis
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.
Offered by

University of Colorado 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.
Start working towards your Master's degree
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