The course will equip you with the competencies and essential skills required to excel in the American Society for Quality (ASQ) Certified Six Sigma Yellow Belt (CSSYB) exam and contribute to process improvement programs. This course focuses on various data collection tools and techniques to analyze data, identify the root causes of a problem, and explore the concepts of measurement system analysis (MSA), and hypothesis testing.
Data Collection and Root Cause Analysis
Give your career the gift of Coursera Plus with $160 off, billed annually. Save today.
Data Collection and Root Cause Analysis
This course is part of ASQ-Certified Six Sigma Yellow Belt Exam Prep Specialization Specialization
Instructors: Skill-Up EdTech Team
Included with 
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Define data requirements to gather relevant data from the process using appropriate data collection methods.
Calculate baseline process performance metrics based on the collected data.
Analyze data for variations and use data analysis tools and techniques to identify the root causes for the problem or variation.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
9 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is part of the ASQ-Certified Six Sigma Yellow Belt Exam Prep Specialization 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
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 4 modules in this course
This module introduces you to descriptive statistics, a branch of statistics that involves summarizing and describing the main features of a dataset. It provides tools and techniques to organize, present, and analyze data to gain insights into its central tendencies, variability, and distribution. Descriptive statistics is fundamental in data analysis and is a basis for more advanced statistical methods. You will also be introduced to inferential statistics. The module also explains the various data types and helps you differentiate between qualitative and quantitative data and data coming from internal and external sources. It describes the data collection process. Further, the module delves into the concept of measurement system analysis (MSA) and its components to understand the variations in the measurement process.
What's included
7 videos2 readings3 assignments1 discussion prompt
This module explains the differences between value-added and non-value-added activities. It makes a case for non-value-added activities that are necessary to enable the smooth running of the organization. The module also discusses how to identify the bottlenecks in a system and suggests ways to eliminate them. Lastly, the module explores the various techniques to conduct a root cause analysis (RCA) for the identified problem in your process or organization. The first one, Pareto analysis, is based on the Pareto principle, which states that approximately 80% of the effects come from 20% of the causes. This analysis helps prioritize potential root causes based on their relative impact. You will also learn how to use the fishbone diagram, also known as the Ishikawa or cause and effect diagram, which visually represents the potential causes contributing to a problem while categorizing the possible causes into specific groups to facilitate the identification of root causes. Additionally, you will learn about the five whys, a simple yet powerful technique involving repeatedly asking “why” to identify the root cause of a problem. It helps to peel the layers of symptoms and surface-level causes to get to the core issue.
What's included
5 videos1 reading3 assignments1 discussion prompt
This module provides a comprehensive overview of hypothesis testing, an essential statistical tool used to assess the validity of claims or hypotheses about populations. You will learn about the hypothesis testing process, its application in real-world scenarios, and how to interpret the hypothesis test results to make better decisions. The module will take you through the different types of hypotheses, types of errors, and the significance of the p-value in hypothesis testing. You will also learn about the principles and applications of correlation and regression techniques. The module discusses the types of correlation and the roles of dependent and independent variables in regression analysis. lt explains the implications of R-squared values in regression analysis. The module also explains simple linear regression and the difference between deterministic and probabilistic models.
What's included
8 videos1 reading3 assignments1 discussion prompt
This is a peer-review assignment based on the concepts taught in the Data Collection and Root Cause Analysis course. In this assignment, you will apply your knowledge of hypothesis testing to a real-life scenario.
What's included
1 video2 readings1 peer review
Offered by
Recommended if you're interested in Data Analysis
Coursera Instructor Network
SkillUp EdTech
SkillUp EdTech
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
New to Data Analysis? Start here.
Open new doors with Coursera Plus
Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.