SITEMAP ABOUT
MiC Quality

ASQ CSSBB Six Sigma Black Belt Certification

  PROCESS IMPROVEMENT AND SIX SIGMA
ONLINE COURSES FREE TRIAL SIX SIGMA FAQ BROCHURES LICENSES ENROLL
SIX SIGMA
:: Online Courses
:: Free Trial
:: Six Sigma
>> Glossary
>> Calculators
>> Reference Tables
>> Book Reviews
>> Black Belt ASQ
:: FAQ
:: Brochures
:: Licenses
:: Discounts
Welcome to MiC Quality Online Learning
Glen Netherwood
MiC Quality
:: Home :: SIX SIGMA :: ASQ SSBB :: CURRENT STUDENTS LOGIN
 
Six Sigma Black Belt ASQ SSBB Body of Knowledge
ASQ SSBB exam contains questions from many topics. These are listed in the Body of Knowledge reproduced below. This version of BOK includes links to Six Sigma Glossary.
I. ENTERPRISE WIDE DEPLOYMENT
II. BUSINESS PROCESS MANAGEMENT
III. PROJECT MANAGEMENT
IV. SIX SIGMA IMPROVEMENT METHODOLOGY AND TOOLS - DEFINE
V. SIX SIGMA IMPROVEMENT METHODOLOGY AND TOOLS - MEASURE
VI. SIX SIGMA IMPROVEMENT METHODOLOGY AND TOOLS - ANALYZE
VII. SIX SIGMA IMPROVEMENT METHODOLOGY AND TOOLS - IMPROVE
VIII. SIX SIGMA IMPROVEMENT METHODOLOGY AND TOOLS - CONTROL
IX. LEAN ENTERPRISE
   
[SIX SIGMA GLOSSARY INDEX OF TOPICS]
V. SIX SIGMA IMPROVEMENT METHODOLOGY AND TOOLS - MEASURE (30 questions)

A. Process Analysis and Documentation

  1. Tools
    Develop and review process maps, written procedures, work instructions, flowcharts, etc. (Analysis)
  2. Process Inputs and Outputs
    Identify process input variables and process output variables and document their relationship through cause-and-effect diagrams, relational matrices, etc. (Evaluation)

B. Probability and Statistics

  1. Drawing valid statistical conclusions
    Distinguish between enumerative (descriptive) and analytical (inferential) studies, and distinguish between a population parameter and sample statistic. (Evaluation)
  2. Central limit theorem and sampling distribution of the mean
    Define the central limit theorem and understand its significance in the application of inferential statistics for confidence intervals, control charts, etc. (Application)
  3. Basic probability concepts
    Describe and apply concepts such as independence, mutually exclusive, multiplication rules, complementary probability, joint occurrence of events, etc. (Application)

C. Collecting and Summarizing Data

  1. Types of Data
    Identify, define, classify, and compare continuous (variables) and discrete (attributes) data, and recognize opportunities to convert attributes data to variables measures. (Evaluation)
  2. Measurement Scales
    Define and apply nominal, ordinal, interval and ratio measurement scales. (Application)
  3. Methods for collecting data
    Define and apply methods for collecting data such as check sheets, coding data, automatic gauging etc. (Evaluation)
  4. Techniques for assuring data accuracy and integrity
    Define and apply techniques for assuring data accuracy and integrity such as random sampling, stratified sampling, sample homogeneity etc. (Evaluation)
  5. Descriptive statistics
    Define, compute and interpret measures of dispersion and central tendency, and construct and interpret frequency distributions and cumulative frequency distributions. (Evaluation) [NOTE: Measures of the geometric and harmonic mean will not be tested]
  6. Graphical methods
    Depict relationships by constructing, applying and intereting diagrams and charts such as stem-and-leaf plots, box-and-whisker plots, run charts, scatter diagrams, etc. and depict distributions by constructing, applying and interpreting diagrams such as histograms, normal probability plots, Weibull plots, etc. (Evaluation)

D. Properties and Applications of Probability Distributions

  1. Distributions commonly used by black belts
    Describe and apply binomial, Poisson, normal, chi-square, Student's t, and F Distributions. (Evaluation)
  2. Other distributions
    Recognize when to use hypergeometric, bivariate, exponential, lognormal and Weibull distributions. (Application)

E. Measurement Systems

  1. Measurement Methods
    Describe and review measurement methods such as attribute screens, gauge blocks, calipers, micrometers, optical comparators, tensile strength, titration, etc. (Comprehension)
  2. Measurement Systems Analysis
    Calculate, analyze, and interpret measurement system capability using repeatability and reproducibility, measurement correlation, bias, linearity, percent agreement, precision/tolerance (P/T), precision/total variation (P/TV), and use both ANOVA and control chart methods for nondestructive, destructive and attribute systems. (Evaluation)
  3. Metrology
    Understand traceability to calibration standards, measurement error, calibration systems, control and integrity of standards and measurement devices. (Comprehension)

F. Analyzing Process Capability

  1. Designing and conducting process capability studies
    Identify, describe, and apply the elements of designing and conducting process capability studies, including identifying characteristics, identifying specifications/tolerances, developing sampling plans and verifying stability and normality. (Evaluation)
  2. Calculating process performance vs. specification
    Distinguish between natural process limits and specification limits and calculate process performance metrics such as percent defective. (Evaluation)
  3. Process capability indices
    Define, select and calculate Cp, Cpk, and assess process capability. (Evaluation)
  4. Process performance indices
    Define, select, and calculate Pp, Ppk, Cpm, and assess process performance. (Evaluation)
  5. Short-term vs. long-term capability
    Understand the assumptions and conventions appropriate when only short-term data are collected and when only attributes data are available; understand the changes in relationships that occur when long term data are used; interpret relationships between long-term and short-term capability as it relates to technology and/or control problems. (Evaluation)
  6. Non-normal data transformations (process capability for non-normal data)
    Understand the cause of non-normal data and determine when it is appropriate to transform. (Application)
  7. Process capability for attributes data
    Compute sigma level and understand its relationship to Ppk. (Application)
SIX SIGMA DEFINE Previous Next SIX SIGMA ANALYZE

FREE Trial
TRY FREE eLearning Module "Introduction to Statistics"
PDF DOWNLOAD FREE Booklet for Primer in Statistics course

OUR COURSES
Advanced Statistics
Statistical Process Control (SPC)
MSA/Gage R&R
Supporting process improvement, quality control, quality assurance, quality management, six sigma training and ASQ certification (CQE, SSBB, SSGB)
Copyright 1998-2014 MiC Quality Legal Notices and Privacy Policy