Lean Six Sigma Green Belt Practice Exam — All Questions

In the Define phase, what is the primary purpose of a project charter?

• a.To calculate the process sigma level
• b.To formally authorize the project and align the team on problem, scope, goal, and business case✓
• c.To document the final control plan
• d.To perform hypothesis testing on the data

The charter is the foundational Define deliverable: it states the problem, scope, goal, business case, team, and timeline so the project is authorized and everyone shares the same objective. Sigma calculations, control plans, and hypothesis tests come in later DMAIC phases.

A SIPOC diagram is used to define which of the following?

• a.The statistical distribution of a critical output
• b.The financial return on the project
• c.The high-level process: Suppliers, Inputs, Process, Outputs, and Customers✓
• d.The root cause of every defect

SIPOC gives a high-level map of Suppliers, Inputs, Process, Outputs, and Customers to bound the process under study. It is a scoping tool, not a statistical, financial, or root-cause analysis tool.

"Critical to Quality" (CTQ) characteristics are best described as:

• a.Measurable product or process features that translate the customer's needs into requirements✓
• b.The team members assigned to the project
• c.The control limits on a process behavior chart
• d.Non-value-added steps in the value stream

CTQs convert the Voice of the Customer into specific, measurable requirements the process must meet. They are derived from customer needs, not from team rosters, control charts, or waste categories.

Which tool helps a Green Belt prioritize which projects or problems to work on by weighting customer requirements against options?

• a.Ishikawa (fishbone) diagram
• b.Control chart
• c.Histogram
• d.Pugh matrix or prioritization matrix✓

A prioritization or Pugh matrix scores options against weighted criteria to guide selection. Fishbone diagrams find causes, control charts monitor stability, and histograms show distribution shape.

A process inspects 500 units, each having 8 opportunities for a defect, and finds 20 defects. What is the DPMO?

• a.2,500
• b.5,000✓
• c.40,000
• d.250

DPMO = defects / (units x opportunities) x 1,000,000 = 20 / (500 x 8) x 1,000,000 = 20 / 4,000 x 1,000,000 = 5,000. Each answer that ignores the opportunity count or the scaling factor is incorrect.

Defects Per Unit (DPU) is calculated as:

• a.Total number of defects divided by total number of units✓
• b.Total number of defects times 1,000,000
• c.Number of units divided by number of defects
• d.Defects divided by the number of opportunities only

DPU = total defects / total units, a simple ratio of how many defects occur per unit produced. Multiplying by a million or dividing by opportunities describes DPMO or DPO, not DPU.

Using the common long-term sigma table (with the 1.5-sigma shift), a process operating at approximately 66,807 DPMO corresponds to what sigma level?

• a.6 sigma
• b.4 sigma
• c.3 sigma✓
• d.2 sigma

On the standard shifted sigma table, roughly 66,807 DPMO equals about a 3-sigma process (about 93.3% yield). Six sigma is about 3.4 DPMO and four sigma is about 6,210 DPMO.

Which type of data is 'the number of scratches found on each painted panel'?

• a.Continuous (variable) data
• b.Nominal data with no order
• c.A specification limit
• d.Discrete (attribute/count) data✓

Counts of defects are discrete attribute data because they take whole-number values. Continuous data (like length or weight) can take any value on a scale, and a count is not a specification limit.

In a Measurement System Analysis (Gage R&R), 'reproducibility' refers to the variation caused by:

• a.The same appraiser measuring the same part repeatedly
• b.Different appraisers measuring the same part with the same gage✓
• c.The natural variation of the manufacturing process
• d.The width of the specification tolerance

Reproducibility is the appraiser-to-appraiser (between-operator) variation. The same appraiser repeating a measurement is repeatability, and neither describes process variation or the tolerance itself.

When testing whether a process change produced a statistically significant effect, a p-value of 0.02 against an alpha of 0.05 means:

• a.Reject the null hypothesis; the result is statistically significant✓
• b.Fail to reject the null hypothesis; no significant effect
• c.The test is invalid and must be repeated
• d.The effect size is guaranteed to be large

Because the p-value (0.02) is less than alpha (0.05), you reject the null hypothesis and conclude the effect is statistically significant. Statistical significance does not by itself measure the size or practical importance of the effect.

A Pareto chart supports the Analyze phase by helping the team:

• a.Prove causation between two variables
• b.Monitor a process over time for stability
• c.Focus on the 'vital few' categories that account for most of the problem✓
• d.Estimate the population standard deviation

The Pareto principle directs attention to the small number of categories that produce the majority of the defects or cost. It does not establish causation, track stability over time, or estimate spread.

A correlation coefficient (r) of 0.85 between two variables indicates:

• a.That one variable definitely causes the other
• b.A strong positive linear relationship between the variables✓
• c.No relationship between the variables
• d.A strong negative linear relationship

An r near +0.85 signals a strong positive linear association, meaning the variables tend to rise together. Correlation alone never proves causation, and a negative relationship would show a negative r.

The '5 Whys' technique is primarily used to:

• a.Calculate process capability indices
• b.Set the sample size for a study
• c.Build a control chart
• d.Drill down from a symptom to an underlying root cause✓

Asking 'why' repeatedly moves the team from the visible symptom toward the deeper root cause. It is a qualitative root-cause tool, not a method for capability, sampling, or control charting.

In hypothesis testing, a Type I error (alpha) occurs when you:

• a.Reject a null hypothesis that is actually true (a false positive)✓
• b.Fail to reject a null hypothesis that is actually false
• c.Choose too large a sample size
• d.Measure a part with the wrong gage

A Type I error is a false positive: concluding an effect exists when it does not, which happens with probability alpha. Failing to detect a real effect is a Type II (beta) error.

A designed experiment (DOE) that studies two factors, each at two levels, in every combination is called a:

• a.One-factor-at-a-time (OFAT) study
• b.Full factorial 2^2 design✓
• c.Fractional factorial design
• d.Simple linear regression

Testing every combination of 2 factors at 2 levels each is a full factorial 2^2 design (four runs). Changing one factor at a time is OFAT, and a fractional factorial deliberately runs only a subset of the combinations.

Poka-yoke, applied in the Improve phase, refers to:

• a.A statistical sampling plan
• b.A capacity-planning calculation
• c.Mistake-proofing that prevents or immediately detects errors✓
• d.A supplier scorecard

Poka-yoke is error- or mistake-proofing that makes a defect impossible or obvious, such as a connector that only fits one way. It is a prevention technique, not a sampling, capacity, or supplier-rating method.

A process has available production time of 480 minutes per shift and customer demand of 240 units per shift. What is the takt time?

• a.0.5 minutes per unit
• b.480 minutes per unit
• c.240 minutes per unit
• d.2 minutes per unit✓

Takt time = available time / customer demand = 480 / 240 = 2 minutes per unit, the pace needed to meet demand. Inverting the ratio or ignoring demand gives the wrong result.

The main purpose of a control chart in the Control phase is to:

• a.Distinguish common-cause variation from special-cause variation over time✓
• b.Rank problems from most to least frequent
• c.Map the suppliers and customers of a process
• d.Prove a factor is statistically significant

Control charts plot data over time with control limits so teams can tell routine common-cause variation from special-cause signals that need action. Ranking, mapping, and significance testing are done with other tools.

A process has USL = 110, LSL = 90, mean = 100, and standard deviation = 2.5. What is the Cp (process capability)?

• a.1.00
• b.1.33✓
• c.0.67
• d.2.00

Cp = (USL - LSL) / (6 x sigma) = (110 - 90) / (6 x 2.5) = 20 / 15 = 1.33. A Cp of 1.33 corresponds to a four-sigma capable process when centered.

In Lean, which of the following is one of the classic categories of waste (muda)?

• a.Standardized work
• b.Value-added processing
• c.Overproduction✓
• d.Continuous flow

Overproduction, making more or sooner than needed, is one of the classic wastes and is often called the worst because it hides others. Standardized work, value-added processing, and continuous flow are goals, not wastes.

The 5S methodology (Sort, Set in order, Shine, Standardize, Sustain) is primarily aimed at:

• a.Designing a full factorial experiment
• b.Calculating rolled throughput yield
• c.Performing a measurement system analysis
• d.Organizing and maintaining an efficient, orderly workplace✓

5S creates and sustains a clean, organized, visual workplace that exposes abnormalities and supports flow. It is a workplace-organization method, not an experimental, yield, or measurement technique.

A control plan created at the end of a project is intended mainly to:

• a.Sustain the gains by specifying what to monitor, how, and the reaction plan if limits are exceeded✓
• b.Define the original problem statement
• c.Replace the need for any ongoing measurement
• d.Calculate the project's net present value

The control plan documents the key characteristics to monitor, the method and frequency, and the response if the process drifts, so improvements hold over time. It defines ongoing monitoring rather than eliminating it, and it is not a Define or finance tool.