SixSigma ASQ

Who Should Take This

It is intended for entry‑level quality professionals, engineers, or project team members who have a basic understanding of improvement concepts but no prior Six Sigma experience. These learners seek to gain a recognized credential that demonstrates their ability to contribute to process improvement projects and advance their career in quality management.

What's Covered

1 All domains in the ASQ Certified Six Sigma Yellow Belt (CSSYB) Body of Knowledge: Six Sigma Fundamentals

2 , Define Phase

3 , Measure Phase

4 , Analyze Phase

5 , and Improve and Control Phases

What's Included in AccelaStudy® AI

Adaptive Knowledge Graph

Practice Questions

Lesson Modules

Console Simulator Labs

Exam Tips & Strategy

20 Activity Formats

Course Outline

65 learning goals

1 Domain 1: Six Sigma Fundamentals

5 topics

Six Sigma Foundations and Principles

Describe the purpose of Six Sigma as a methodology for reducing variation and defects in processes, including the evolution from quality pioneers such as Shewhart, Deming, Juran, and Motorola.
Explain the DMAIC methodology phases (Define, Measure, Analyze, Improve, Control) and how each phase contributes to structured problem solving in process improvement projects.
Apply the Six Sigma value proposition to organizational scenarios by connecting variation reduction and defect elimination to measurable business outcomes such as cost savings and customer satisfaction.
Differentiate between Six Sigma and other quality improvement methodologies such as Total Quality Management and Lean, identifying where each is most effective and how they complement each other.

Lean Foundations and Principles

Identify the seven elements of waste (muda) in Lean methodology: overproduction, correction, inventory, motion, overprocessing, conveyance, and waiting, with examples of each in production and service environments.
Explain Lean methodologies including just-in-time production, poka-yoke error proofing, kanban pull systems, and value stream mapping, and describe how each eliminates waste in process flows.
Analyze a process scenario to identify which of the seven Lean wastes are present and recommend appropriate Lean tools for waste elimination and process flow improvement.
Describe the 5S workplace organization methodology (sort, set in order, shine, standardize, sustain) and explain how each step contributes to waste reduction and workplace efficiency.

Roles and Responsibilities

Identify the Six Sigma belt hierarchy roles including Yellow Belt, Green Belt, Black Belt, and Master Black Belt, and describe the responsibilities and scope of each within a project organization.
Describe the supporting roles of process owner, champion, and sponsor in Six Sigma deployments and explain how each role contributes to project success and organizational alignment.
Apply role selection criteria to determine which belt level and supporting roles are needed for a given project based on complexity, scope, and organizational requirements.

Team Basics

Identify the types of Six Sigma teams including continuous improvement teams, self-managed teams, and cross-functional teams, and describe when each team structure is most effective.
Explain the five stages of team development (forming, storming, norming, performing, adjourning) and identify team behaviors and leadership actions appropriate to each stage.
Apply decision-making tools including brainstorming, multivoting, and nominal group technique to facilitate team consensus on prioritization and problem-solving activities.
Describe effective team communication methods including meeting agendas, minutes, and project status reports and explain their role in maintaining project momentum and stakeholder alignment.

Quality Tools and Six Sigma Metrics

Identify the seven basic quality tools (Pareto charts, cause-and-effect diagrams, flowcharts, run charts, check sheets, scatter diagrams, histograms) and describe the purpose and appropriate use of each.
Apply the seven basic quality tools to process improvement scenarios by selecting the appropriate tool for data collection, analysis, or visualization based on the type of problem being investigated.
Calculate and interpret Six Sigma metrics including defects per unit (DPU), defects per million opportunities (DPMO), rolled throughput yield (RTY), cycle time, and cost of poor quality (COPQ).
Analyze process performance using Six Sigma metrics to determine whether a process meets quality targets and identify areas requiring improvement intervention.
Explain the relationship between sigma level, DPMO, and process yield, and describe how organizations use sigma level as a benchmark for process maturity.

2 Domain 2: Define Phase

2 topics

Project Identification

Explain how to define customer needs using voice of the customer (VOC) methods and translate them into critical-to-quality (CTQ) characteristics that drive project selection.
Apply project selection criteria to identify and prioritize candidate DMAIC projects based on business impact, feasibility, and alignment with organizational goals.
Identify stakeholders including end users, subject matter experts, process owners, and affected parties, and describe the purpose and methods of stakeholder analysis in project scoping.
Construct a SIPOC diagram (suppliers, inputs, process, outputs, customers) to define high-level process boundaries, inputs, and outputs for a Six Sigma project.
Describe the relationship between supply chain management and Six Sigma project management, identifying how upstream and downstream processes affect project scope.

Project Management Basics

Describe the components of a project charter including problem statement, scope, baseline data, goals, and team composition, and explain how the charter guides project execution.
Explain the purpose and benefits of a communication plan for Six Sigma projects and describe how it supports stakeholder engagement and project transparency.
Apply project planning tools including work breakdown structures (WBS) and Gantt charts to decompose project scope, schedule activities, and track progress through DMAIC phases.
Identify management and planning tools including activity network diagrams, affinity diagrams, matrix charts, relations charts, and tree diagrams, and select the appropriate tool for a given planning need.
Explain the purpose and process of tollgate or phase reviews within the DMAIC lifecycle and describe what deliverables must be completed before proceeding to the next phase.
Analyze a project charter to evaluate whether the problem statement, scope, and goals are sufficiently specific and measurable to support a successful DMAIC project.

3 Domain 3: Measure Phase

3 topics

Basic Statistics

Calculate and interpret measures of central tendency (mean, median, mode) for process data sets and explain when each measure is most appropriate for summarizing data.
Calculate and interpret measures of dispersion (standard deviation, range, variance) and explain how dispersion quantifies process variability.
Analyze the relationship between measures of central tendency and dispersion to characterize process behavior and identify whether a process is centered and predictable.

Data Collection

Develop a data collection plan that specifies operational definitions, data sources, gathering methods, and collection frequency appropriate to a Six Sigma project.
Differentiate between qualitative and quantitative data types and select appropriate data collection techniques (surveys, interviews, check sheets, checklists) for each type.
Explain the importance of operational definitions in ensuring data consistency and describe how ambiguous definitions lead to measurement errors in process analysis.

Measurement System Analysis

Define measurement system analysis terms including precision, accuracy, bias, linearity, and stability, and explain why each property is important for data integrity in Six Sigma projects.
Explain the concepts of gauge repeatability and reproducibility (GR&R) and describe how GR&R studies assess whether a measurement system is adequate for process analysis.
Analyze GR&R study results to determine whether observed process variation is attributable to the measurement system or to actual process variation.

4 Domain 4: Analyze Phase

5 topics

Process Analysis Tools

Apply 5S methodology (sort, set in order, shine, standardize, sustain) and value analysis techniques to identify non-value-added activities and workspace inefficiencies in a process.
Construct and interpret a Failure Mode and Effects Analysis (FMEA) by assigning severity, occurrence, and detection ratings and calculating the risk priority number (RPN) to prioritize corrective actions.
Explain how process maps and flowcharts are used in the Analyze phase to identify bottlenecks, rework loops, and redundant steps in current-state processes.

Root Cause Analysis

Apply the 5 Whys technique to systematically drill down from a problem statement to its fundamental root cause through iterative questioning.
Apply root cause analysis methods including process mapping, 8D methodology, force-field analysis, and matrix charts to systematically trace defects and process failures to their origin.
Evaluate root cause analysis findings to determine which identified causes are most likely to be true root causes versus symptoms and select appropriate verification methods.

Corrective and Preventive Action

Describe the corrective action process steps: problem identification, containment, root cause determination, permanent solution implementation, verification, and effectiveness validation.
Explain the preventive action process including identifying potential failures using FMEA and other analysis techniques, implementing preventive improvements, and verifying their effectiveness.
Differentiate between corrective action (reactive, addressing existing nonconformances) and preventive action (proactive, preventing potential nonconformances) in process improvement.

Data Analysis

Identify and describe common distribution types including normal and binomial distributions and recognize skewed and bimodal distribution shapes in process data histograms.
Differentiate between common cause variation (inherent to the process) and special cause variation (assignable external factors) and explain the implications of each for process stability.
Interpret graphical displays including histograms, box plots, and run charts to identify patterns, trends, and outliers in process data.

Correlation, Regression, and Hypothesis Testing

Explain how correlation analysis identifies relationships between process variables and interpret scatter diagrams to assess the strength and direction of variable associations.
Describe the basic concepts of regression analysis and explain how regression models predict process outcomes based on input variable relationships.
Explain hypothesis testing concepts including null and alternative hypotheses, Type I and Type II errors, p-value interpretation, and statistical power in the context of process improvement decisions.
Differentiate between correlation and causation when analyzing process variables and explain why establishing a causal relationship requires more than a strong correlation coefficient.

5 Domain 5: Improve and Control Phases