Six Sigma Tools for Analyze (Coursera)

Six Sigma Tools for Analyze (Coursera)

This course will cover the Measure phase and portions of the Analyze phase of the Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) process. You will learn about lean tools for process analysis, failure mode and effects analysis (FMEA), measurement system analysis (MSA) and gauge repeatability and reproducibility (GR&R), and you will be introduced to basic statistics. This course will outline useful measure and analysis phase tools and will give you an overview of statistics as they are related to the Six Sigma process.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

The statistics module will provide you with an overview of the concepts and you will be given multiple example problems to see how to apply these concepts. Every module will include readings, discussions, lecture videos, and quizzes to help make sure you understand the material and concepts that are studied.
Our applied curriculum is built around the latest handbook The Certified Six Sigma Handbook (2nd edition) and students will develop /learn the fundamentals of Six Sigma. Registration includes online access to course content, projects, and resources but does not include the companion text The Certified Six Sigma Handbook (2nd edition). The companion text is not required to complete the assignments. However, the text is a recognized handbook used by professionals in the field. Also, it is a highly recommended text for those wishing to move forward in Six Sigma and eventually gain certification from professional agencies such as American Society for Quality (ASQ).
Course 3 of 4 in the Six Sigma Yellow Belt Specialization.

Syllabus

WEEK 1
Measurement System Analysis
Welcome to Six Sigma Tools for Analyze! This is the third course in the Six Sigma Yellow Belt Specialization. Your team of instructors, Dr. Bill Bailey, Dr. David Cook, Dr. Christine Scherrer, and Dr. Gregory Wiles, currently work in the College of Engineering and Engineering Technology at Kennesaw State University. This module will introduce you to Measurement System Analysis (MSA) which is a key component of the Measure phase of the DMAIC process. You will also learn about Gauge Repeatability & Reproducibility (GR&R) and why it is used in the measurement phase.

WEEK 2
Process Analysis Tools
This module will introduce you to the Analysis phase of the DMAIC process. Process analysis helps you to better understand current processes and how they can be improved. You will be introduced to many of the different process analysis tools that are commonly used by Six Sigma experts. Failure Mode and Effects Analysis (FMEA) will also be introduced to help you better understand how to identify process failures.

WEEK 3
Root Cause Analysis
Root cause analysis is a common problem solving step. Determining the root cause of something is an important aspect of uncovering the causes of a problem. In this module you will review the different tools used in determining root cause including 5-whys, process mapping, force-field analysis, and matrix charts.

WEEK 4
Data Analysis
In this module you will be diving into the statistical side of Six Sigma. You will begin with learning about the basic distribution types which include normal and binomial. You will then proceed to variation and will learn the difference between common and special cause variation.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Population Health: Predictive Analytics (Coursera) Coursera
Leiden University

Population Health: Predictive Analytics (Coursera)

Predictive analytics has a longstanding tradition in medicine. Developing better prediction models is a critical step in the pursuit of improved health care: we need these tools to guide our decision-making on preventive measures, and individualized treatments. In order to effectively use and develop these models, we must understand them better. In this course, you will learn how to make accurate prediction tools, and how to assess their validity. First, we will discuss the role of predictive analytics for prevention, diagnosis, and effectiveness. Then, we look at key concepts such as study design, sample size and overfitting.

Nov 23rd 2026
4 Weeks
Empathy, Data, and Risk (Coursera) Coursera
University of Illinois at Urbana-Champaign

Empathy, Data, and Risk (Coursera)

Risk Management and Innovation develops your ability to conduct empathy-driven and data-driven analysis in the domain of risk management. This course introduces empathy as a professional competency. It explains the psychological processes that inhibit empathy-building and the processes that determine how organizational stakeholders respond to risk.

Nov 23rd 2026
4 Weeks
Combining and Analyzing Complex Data (Coursera) Coursera
University of Maryland, College Park

Combining and Analyzing Complex Data (Coursera)

In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be covered with R® receiving particular emphasis. The course will also cover the basics of record linkage and statistical matching—both of which are becoming more important as ways of combining data from different sources. Combining of datasets raises ethical issues which the course reviews. Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries.

Nov 16th 2026
4 Weeks
Causal Inference (Coursera) Coursera
Columbia University

Causal Inference (Coursera)

This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the way in which statisticians and applied researchers in many disciplines use data to make inferences about causal relationships.

Nov 16th 2026
5-12 Weeks
Gestión del análisis de datos (Coursera) Coursera
Johns Hopkins University

Gestión del análisis de datos (Coursera)

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results.

Nov 16th 2026
1 Week
Basic Statistics (Coursera) Coursera
University of Amsterdam

Basic Statistics (Coursera)

Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression.

Nov 23rd 2026
5-12 Weeks
Doing Economics: Measuring Climate Change (Coursera) Coursera
University of London,University College London,CORE

Doing Economics: Measuring Climate Change (Coursera)

This course will give you practical experience in working with real-world data, with applications to important policy issues in today’s society. Each week, you will learn specific data handling skills in Excel and use these techniques to analyse climate change data, with appropriate readings to provide background information on the data you are working with. You will also learn about the consequences of climate change and how governments can address this issue.

Nov 16th 2026
4 Weeks
Analyzing and Visualizing Data in Looker (Coursera) Coursera
Google Cloud

Analyzing and Visualizing Data in Looker (Coursera)

In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

Nov 23rd 2026
2 Weeks
Necessary Condition Analysis (NCA) (Coursera) Coursera
Erasmus University Rotterdam

Necessary Condition Analysis (NCA) (Coursera)

Welcome to Necessary Condition Analysis (NCA). NCA analyzes data using necessity logic. A necessary condition implies that if the condition is not in place, there will be guaranteed failure of the outcome. The opposite however is not true; if the condition is in place, success of the outcome is not guaranteed.

Nov 23rd 2026
5-12 Weeks
Process Mining: Data science in Action (Coursera) Coursera
Eindhoven University of Technology

Process Mining: Data science in Action (Coursera)

Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis.

Nov 16th 2026
5-12 Weeks