
Draft the problem statement, process boundary and pending sponsor decisions.
Calculate the direct rework baseline and label annual exposure as a conditional projection.
Prepare a charter draft with its data basis and unresolved approvals.
Tools in this lecture: Project Charter and COPQ Builder.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Build a SIPOC boundary and keep unconfirmed customer requirements visible.
Map processing and waiting time; distinguish processing share from value-added classification.
Calculate takt from one daily time-and-demand basis and record a waste observation.
Tools in this lecture: Value Stream and Takt Calculator.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Define the reading, unit, sampling frame and selection method.
Plan estimation precision for a mean or proportion, with assumptions stated.
Prepare a traceable collection record and identify missing measurement details.
Tools in this lecture: Sampling and Data Plan Planner.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Inspect a balanced crossed Gage R&R study using repeated readings and retained interaction.
Distinguish study-variation and tolerance comparisons; inspect pairwise rating agreement.
Write a measurement assessment without assuming calibration, stability or approval.
Tools in this lecture: Gage R&R Calculator.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Count observed specification failures and inspect distribution and observation order.
Compare within-subgroup capability and overall performance indices with their different denominators.
Report unsupported defect opportunities and unaccepted forecasts explicitly.
Tools in this lecture: Process Capability Calculator.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Rank recorded errors with Pareto and compare category composition across shifts.
Inspect station variation, then organize possible causes and an evidence why-chain.
Record a supported candidate explanation, alternatives and a check that could disprove it.
Tools in this lecture: Pareto and Root Cause Analyzer.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Select a route for means, paired times, proportions, contingency counts or one-way ANOVA.
Read effects, intervals and conditional test results while retaining assumptions.
Record the next evidence check and use the labelled approximation to plan a paired study.
Tools in this lecture: Hypothesis Test Calculator.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Fit a simple relationship, inspect residuals and keep predictions within their stated scope.
Compare a two-by-two factorial study, main effects and interaction; multiple predictors remain an overview.
Plan future run order and confirmation without inventing the historical randomization log.
Tools in this lecture: Regression and DOE Calculator.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Compare candidate changes and record process failure modes, missing ratings and pilot criteria.
Read before-and-after results using their actual volumes and distinguish both rework benefit bases.
Document a human implementation decision with unresolved costs, authority and causal limits.
Tools in this lecture: FMEA and Pilot Scorecard.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
Choose among X-bar/R, I-MR, p, np, c and u modes using the supported study and reference datasets.
Review chart signals and retain old limits until a reasoned change is accepted.
Draft the control plan, response and owner handover without inventing authority or acceptance.
Tools in this lecture: Control Chart Builder.
Download the lesson PDF and the interactive HTML tool from the lecture resources.
This course contains the use of artificial intelligence
$513 a week. That is what one small packing process in this course loses to rework, and it is the first number you will calculate yourself.
Then the course makes you prove every step that follows.
Most Green Belt training stops at the tools. You watch a definition, a formula and a screen in paid statistics software. Then you go back to work and nobody has shown you how the charter connects to the gage study, or why the capability number means little until the measurement is trusted. You are asked to lead an improvement project, and you have never seen one run from the first page to the last.
Here you walk one complete DMAIC project on one set of data. A fictional food bank has boxes that miss their weight limits and orders that go out wrong. You scope the problem, test the measurement, read the capability, chase the cause, pilot the fix and hand the process to its owner.
This data does not behave nicely, and that is the point:
After this course you can walk into a project review with a charter, a measurement assessment, a capability baseline, a tested cause, a pilot decision and a control plan, and explain every number on them.
No paid software, no trial. Every lesson comes with its own offline HTML tool that recalculates as you edit, with the Excel formula beside the calculation, so you can reproduce the work in a spreadsheet you already have.
Who teaches this
Mike is an educator, not a Six Sigma belt holder. The method here comes from published sources, led by the NIST/SEMATECH e-Handbook of Statistical Methods, and every constant is traced to its source.
The path
First you define the project: charter, cost of poor quality, customer needs and the value stream. Then you measure: a sampling plan, a Gage R&R study and a capability baseline. Next you analyze: Pareto charts, stratification, hypothesis tests, regression and a two-factor experiment. You improve with mistake-proofing, FMEA and a pilot. Finally you control: charts, signal rules, a control plan and a handover.
What's included
About certification
This independent course prepares you against selected topics in the published ASQ Certified Six Sigma Green Belt Body of Knowledge (2022) and IASSC Green Belt Body of Knowledge, within the scope stated in the course coverage map. It does not cover every topic or guarantee an exam pass. Completing this course does not award Green Belt certification. Neither the course nor its provider is accredited by ASQ, IASSC, or PeopleCert.
In practice, this means one DMAIC project at Green Belt level, not complete exam preparation. Topics such as nonparametric tests, Design for Six Sigma, QFD, advanced regression, X-bar S, CuSum and EWMA charts are not taught here. Compare the published body of knowledge with these lessons before you sit any exam.
Every month without a working project is another month of the same rework and the same guesses. The price of this course can change, and your colleagues are already learning to bring numbers to the table.
Enroll now and start your first lesson today.