The Six Sigma Black Belt body of knowledge is the list of topics a Black Belt is expected to know. It covers how to select and charter projects, plan data collection and test hypotheses. It also covers ANOVA, regression, experiments, Lean flow, handing over a controlled process and leading change. Several professional bodies publish their own outlines, and they overlap heavily but are not identical. This guide walks through the shared core area by area. A worked half-fraction experiment shows what one area looks like in practice. It ends with a free course that covers the same ground.
We could not open ASQ's own outline page when this guide was written (1 November 2026). So it describes the common core and does not quote any body's current list or exam rules. Read the current outline of the body you plan to use. Names and marks belong to their owners.
What a body of knowledge is, and is not
A body of knowledge (BoK) is a syllabus written by a professional body. It lists topics and the depth expected, usually as verbs: define, calculate, interpret, evaluate. It is not a textbook and not a method. Two bodies can teach the same tools and weight them differently, so a topic list from one may not match an exam from another.
The ASQ Black Belt page and the IASSC site are the usual starting points for outlines. Companies also run in-house Black Belt programmes with their own lists. The honest way to compare programmes is to compare topic lists, not names.
The common core, area by area
| Area | The question it answers | Typical tools |
|---|---|---|
| Project selection and charter | Is this worth doing, and for whom? | Benefit estimate, project scoring, charter, CTQ tree |
| Data and sampling | What must we measure, and how much? | Sampling plan, sample size, measurement checks |
| Probability and distributions | What does the data look like? | Normality tests, transformations, capability |
| Hypothesis tests | Is the difference real? | t-tests, proportions, chi-square, power |
| ANOVA and regression | Which factors matter, and how much? | One-way and two-way ANOVA, multiple and logistic regression |
| Designed experiments | What settings give the best result? | Full and fractional factorial designs |
| Lean flow | Where does time go? | Value stream map, takt, pull, kanban sizing |
| Control, change and coaching | How do we keep the gain? | Control plan, SPC, change leadership, coaching |
Each row builds on the one above. You cannot size a sample before you know what to measure, and you cannot design an experiment before the measurement system is trusted. That order is the reason Black Belt material is taught as a sequence rather than a menu.
A worked example from the experiments area
Designed experiments are where Black Belt study departs most from Green Belt study. Suppose three settings of a moulding process, each at a low (-1) and high (+1) level, could affect part strength. A is temperature, B is hold time and C is pressure. A full set of runs needs 2 x 2 x 2 = 8 trials. A half fraction uses 4 trials, choosing the pattern so that C equals the product of A and B.
| Run | A | B | C = A x B | Strength |
|---|---|---|---|---|
| 1 | -1 | -1 | +1 | 52 |
| 2 | +1 | -1 | -1 | 66 |
| 3 | -1 | +1 | -1 | 48 |
| 4 | +1 | +1 | +1 | 74 |
The effect of a factor is the average at its high level minus the average at its low level. For A, the average at high is (66 + 74) / 2 = 70 and at low is (52 + 48) / 2 = 50, so the effect is 20. For B, high is (48 + 74) / 2 = 61 and low is (52 + 66) / 2 = 59, so the effect is 2. For C, high is (52 + 74) / 2 = 63 and low is (66 + 48) / 2 = 57, so the effect is 6.
The catch is aliasing. Because C was built from A x B, the effect we call C is also the A-by-B interaction. We cannot tell them apart from four runs. In the same way, A is mixed up with B x C and B with A x C. This is a resolution III design: main effects are mixed up with two-factor interactions. That is acceptable when you screen many factors and expect interactions to be small, and unacceptable when you suspect a strong interaction. Reading this trade-off correctly is exactly what a Black Belt syllabus tests. The numbers above were computed in node and can be checked in a spreadsheet.
A second example: how much data
The data area asks how many measurements are enough. To estimate a proportion at 95% confidence, a safe size is n = z squared x p x (1 - p) / e squared. Use z = 1.96, and p = 0.5 when you know nothing about p. For a margin of 5 percentage points, n = 3.8416 x 0.25 / 0.0025 = 384.2, so 385 observations. For 3 points, n = 3.8416 x 0.25 / 0.0009 = 1,067.1, so 1,068. Tightening the margin from 5 to 3 points nearly triples the data, and the cost grows with it.
How the pieces connect in a real project
A Black Belt project might start with a charter that states a benefit in cost units. It moves to a data plan, then finds with ANOVA that one machine differs. A small experiment finds a better setting, and a control plan makes the gain last. The tools are not separate lessons. They are steps in one chain of evidence, and a weak step early on, such as an untested measurement system, undermines every step after it. Our post on AI quality inspection in manufacturing shows one place where those measurement questions arise in practice.
Free software for the practice
Everything above can be done in a spreadsheet such as Excel or LibreOffice Calc. JASP is a free, open-source statistics program that gives full ANOVA and regression output. Minitab is common in industry and offers a free trial on its own site, so check its current terms there. A project plan, change log and risk list help too, and a RAID log example shows one way to keep them.
How to use an outline to study
Treat the outline as a checklist, not a reading list. For each topic, ask whether you can do three things. Explain it in plain words, calculate it by hand on a small data set, and say when it would be the wrong tool. If you can only do the first, you know the vocabulary. If you can do all three, you know the topic.
A good habit is to keep one running data set for the whole programme. A set of fill weights, cycle times or defect counts can be reused for a sampling plan, a normality check, a t-test, an ANOVA and a regression. Seeing the same numbers answer different questions makes the links between areas clear, and it exposes weak spots quickly.
Common misreadings of the outline
- Believing every tool must appear in every project. A Black Belt picks the smallest tool that answers the question, and many projects never need an experiment.
- Reading a verb such as "interpret" as "run the software". Interpretation means saying what the output allows you to conclude and what it does not.
- Treating Lean and Six Sigma as rivals. Lean flow tools find where time is lost, and the statistical tools find why results vary. Most real problems have both.
- Memorising formulas without units. Every number in the worked examples above has a unit or a count, and a result without one cannot be checked.
Learn the Black Belt topics free
The free Lean Six Sigma Black Belt course covers the Black Belt body of knowledge in 12 study modules and a final assessment. Early modules cover charters, project selection, data collection and non-normal data. Later ones cover hypothesis tests with power, ANOVA, regression, factorial experiments and Lean flow. The last ones cover control plans, change leadership and a full improvement case. It prepares you for exams in the style of ASQ and IASSC, and it assumes the Green Belt toolkit. If that is new, start with the free Six Sigma Green Belt training.
It is a free course with a verifiable certificate of completion, and anyone can check a certificate on our verification page. It is not a credential from any professional body, and EDWartens is not affiliated with ASQ, IASSC or Minitab. Begin the Black Belt course once you can run a simple t-test.
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Questions
What is the Six Sigma Black Belt body of knowledge?
It is the syllabus a professional body publishes for Black Belt level: project selection, data and sampling, hypothesis tests, ANOVA, regression, designed experiments, Lean flow, control plans and change leadership. Different bodies publish different lists, so compare topics, not names.
Is the Black Belt body of knowledge the same for every exam?
No. ASQ, IASSC and company programmes overlap heavily but weight and word topics differently. Read the current outline of the body whose exam or programme you plan to use.
What is a fractional factorial design?
It is an experiment that runs only a fraction of all combinations of factor levels. A half fraction of three two-level factors uses 4 runs instead of 8. The saving costs clarity, because some effects are aliased and cannot be separated.
How many samples do I need to estimate a proportion?
With no prior estimate, use n = 1.96 squared x 0.25 divided by the margin squared. A margin of 5 percentage points needs 385 observations and 3 points needs 1,068, at 95 percent confidence.
Can I learn the Black Belt topics for free?
Yes. The free Lean Six Sigma Black Belt course on EDWartens covers the body of knowledge in 12 study modules and a final, and you can practise in a spreadsheet or JASP. Any exam fee for a professional body's exam is paid to that body.
Is the EDWartens certificate a Black Belt credential?
No. It is a verifiable certificate of completion for the course, with a unique number, QR code and public verification page. It is not a credential from ASQ, IASSC or any other body.
Sources
- ASQ: Six Sigma Black Belt certification (page not opened on 1 November 2026)
- IASSC (read 1 November 2026)
- JASP: free statistics software (read 1 November 2026)
Written by the EDWartens engineering team for general education. Product names are trademarks of their owners; mentioning them does not imply endorsement. Prices and terms of other providers were checked on the date shown and can change.
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