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Certiprof Lean Six Sigma White Belt Professional Certification Exam Answers

Certiprof Lean Six Sigma White Belt Professional Certification Exam Answers

In this certification, the candidate will be able to learn the basics of Lean Six Sigma, understand basic statistical concepts related to this methodology, identify the steps of the DMAIC cycle, and understand the basic concepts to achieve process improvement.

Learning Objectives:

Enable students to learn about the fundamental concepts of Lean Manufacturing and Six Sigma

Audience Profile:

  • Quality Managers
  • Managers and heads of continuous improvement
  • Industrial engineers
  • Process engineers
  • Any professional who wishes to learn about continuous improvement methodologies

Exam Details: Lean Six Sigma White Belt Professional Certification

  • Format: Multiple choice
  • Open Book: No
  • Questions: 40
  • Language: English
  • Passing Score: 80%
  • Duration: 60 minutes
  • Delivery: This examination is available Online
  • Synchronous.
  • Cyclical.
  • Is performed once.
  • Cascade.
  • Champion, White, Yellow, Green, Green,Black, Master Black.
  • White, Green, Yellow, Black, Master Black, Champion.
  • White, Yellow, Green,Black, Master Black.
  • White, Yellow,Green, Black, Master Black, Champion.
  • Define, Measure, Analyze, Control, Improve.
  • Define, Measure, Analyze, Improve, Control.
  • Measure, define, analyze, improve, control.
  • Define, measure, improve, analyze, control.
  • 7.
  • 6.
  • 5.
  • 2.
  • Output.
  • Causes.
  • The problem.
  • Sigma level.
  • Continuous.
  • Continuous and Discrete.
  • Evaluated.
  • Discrete.
  • Scrum.
  • Strategic organization.
  • Continuous improvement.
  • None of the above.
  • Evaluated.
  • Measured.
  • Verified.
  • Counted.
  • Effectiveness.
  • Process Capability.
  • Attributes.
  • A and B are correct.
  • A and C are correct.
  • Measure.
  • Improve.
  • Control.
  • Analyze.
  • Extra-processing.
  • Waiting.
  • Overproduction.
  • Transportation.
  • Variance.
  • Standard Deviation.
  • Range.
  • Mean.
  • Define, Measure, Analyze, Improve, Control.
  • Define, Measure, Analyze, Organize, Control.
  • Define, measure, analyze, improve, check.
  • Define, analyze, improve, control.
  • Mean.
  • Spread.
  • Mode.
  • Median.
  • Rework.
  • Transportation.
  • Overproduction.
  • Motion.
  • Waste.
  • Lean.
  • DPMC.
  • DPMO.
  • Knowing the basic concepts of Lean Six Sigma.
  • Assist Green Belts in specific processes.
  • Project Management.
  • All of the above.
  • Causes.
  • The problem.
  • Sigma level.
  • Input.
  • Project management.
  • The basic concepts of Lean Six Sigma.
  • Identify what about the process is not working as it should.
  • All quality tools.
  • Higher.
  • Lower.
  • Both options.
  • None of the above.
  • Train black belts and green belts.
  • Have many years of experience.
  • Add resources to the project.
  • All of the above.
  • Mode.
  • Spread.
  • Median.
  • Mean.
  • Add resources to the project.
  • Know the basic concepts of Lean Six Sigma.
  • Lead a team.
  • Manage the project.
  • All of the above.
  • Discrete Data.
  • Diminished data.
  • Continuous Data.
  • Attributes.
  • Number of opportunities in a sample divided by the total number of defect opportunities multiplied by 1million.
  • Number of defects in a sample divided by the total number of defects of defects multiplied by 1million.
  • Number of defects in a sample divided by the total number of defect opportunities multiplied by 1million.
  • Number of opportunities in a sample divided by the total number of defects of defects multiplied by 1million
  • Define root cause.
  • Define KPIs.
  • Analyze the data collected.
  • The problem to work on is clearly defined.
  • Analyze.
  • Improve.
  • Measure.
  • Control.
  • Shape, center and spread.
  • Shape and limits.
  • Spread and limits.
  • Shape and spread.
  • Interpret and draw conclusions from the population.
  • Evaluate the data.
  • Evaluate control limits.
  • Understand or map data from a sample or population.
  • ±6σ
  • ±3σ²
  • ±6σ²
  • ±3σ
  • Median.
  • Standard Deviation.
  • Variance.
  • Mean.
  • Scrum.
  • DMAIC.
  • Lean.
  • None of the above.
  • Counted.
  • Measured.
  • All of the above.
  • None of the above.
  • Apple.
  • Lenovo.
  • Motorola.
  • Toyota.
  • Extra-processing.
  • Motion.
  • Overproduction.
  • Transportation.
  • Decreases, Increases.
  • Decreases. Decreases.
  • Increases, Increases.
  • None of the above.
  • Lean.
  • DMAIC.
  • Scrum.
  • None of the above.
  • We record the selected data.
  • We analyze metrics.
  • We identify the root cause.
  • We follow up on the implemented actions.
  • Variance.
  • Mean.
  • Range.
  • None of the above.
  • All of the above.
  • Measure parameters.
  • Define KPIs.
  • Identify the reasons why something is going wrong.
  • The problem to be addressed is defined.
  • Identify what in the process is not working as it should.
  • Identify the root cause of a problem.
  • Adding resources to the project.
  • All of the above.
  • Lean.
  • DMAIC.
  • DPMO.
  • Six Sigma.
  • Waste.
  • The data.
  • Overprocesses.
  • Processes.
  • Understand or map data from a sample or population.
  • Evaluate the data.
  • Evaluate samples.
  • Making decisions about a population based on the parameters or characteristics of a sample.
  • Analyze.
  • Measure.
  • Control.
  • Check.
  • Bob Galvin.
  • Bill Smith.
  • Taiichi Ono.
  • None of the above.
  • Analyze.
  • Control.
  • Measure.
  • Define.
  • Lean.
  • Lean Six Sigma.
  • Six Sigma.
  • None of the above.
  • Control.
  • Measure.
  • Analyze.
  • Improve.
  • Measure.
  • Define.
  • Analyze.
  • Control.
  • Discrete.
  • Evaluated.
  • Continuous.
  • Continuous and Discrete.
  • Lean Six Sigma.
  • Lean Methodology.
  • DMAIC.
  • Six Sigma.
  • We make decisions to analyze the root cause.
  • Analyze metrics.
  • We set control limits.
  • Make decisions that lead to change the current situation.
  • Extra-processing.
  • Waiting.
  • Sigma.
  • Motion.
  • Knowing the basic concepts of Lean Six Sigma.
  • Project management.
  • Support Green Belt in specific processes.
  • Identify what about the process is not working as it should.
  • It’s off the charts.
  • It has poor performance.
  • It has a 99.9% performance.
  • None of the above.
  • Largest number of DPMO.
  • Least number of DPMO.
  • Level and Number of DPMO equal.
  • None of the above.
  • Six Sigma.
  • Variance.
  • Sigma.
  • Lean.
  • Range.
  • Median.
  • Mode.
  • Range.
  • None of the above.
  • All of the above.
  • Descriptive Statistics.
  • Inferential Statistics.
  • Statistics.
  • Differential Statistics.
  • Overproduction, transportation, inventory, scrap, extra-processing, rework, motion.
  • Overproduction, transportation, inventory, waiting,extra-processing, rework, motion.
  • Overproduction, transportation, inventory, waiting, extra-processing, push, pull.
  • Overproduction, transportation, inventory, waiting, extra-processing, rework, suspect material.
  • Additional additions to the work.
  • Any amount above the minimum necessary to get the job done.
  • Repetitions of work.
  • All of the above.
  • None of the above.
  • Spread.
  • Median.
  • Mode.
  • Mean.
  • X Century.
  • 21st Century.
  • 20th Century.
  • XXV Century.
  • Reduce defects.
  • Collect metrics to understand the situation.
  • Analyze and define the problem.
  • Analyze the information.
  • Methodology that aims to eliminate waste and improve processes.
  • Methodology that seeks to improve processes.
  • Methodology that seeks to reduce waste and improve processes.
  • Methodology whose principle is to evaluate the wastes.
  • Identify what about the process is not working as it should.
  • Knowing the basic concepts of Lean Six Sigma.
  • Support Black Belts in specific processes.
  • Identifying the root cause of a problem.
  • All of the above.
  • Put Lean Six Sigma processes and methods into practice.
  • Evaluate metrics on a daily basis.
  • Add resources to the project.
  • All of the above.
  • Attributes.
  • Discrete Data.
  • Continuous Data.
  • Diminished data.
  • Differential Statistics.
  • Statistics.
  • Inferential Statistics.
  • Descriptive Statistics.

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