Programs

Black Belt

Program Description

Black Belts are highly trained Six Sigma experts who possess the knowledge and skills that are necessary to facilitate breakthrough improvements in key processes that support the overall aims of an enterprise or operating unit. They serve as change agents, internal consultants, mentors to Green Belts and assistants to Six Sigma Champions. Black Belts optimize existing technology, or bring new technologies on line at optimal operating conditions and are the masters of problem solving. They have the technical and leadership capability to improve the performance of an existing industrial or commercial process, regardless of complexity or output volume. They also tackle and solve specific process-oriented or design-centric problems that have a negative impact on customer satisfaction, operational capability, output capacity, cycle time and other performance-related metrics.

Students will focus on obtaining an in-depth understanding of the Six Sigma principles and implementation tactics, along with advanced applications in the areas of descriptive statistics, benchmarking, process control techniques, process diagnostic methods and experimental design. You will learn the importance of quantitative data and its vital role in successful problem solving, as well as the importance of sample size and how to administer a sampling scheme. You will discover how the key tools are blended and sequenced to form a scientific and repeatable process for solving critical manufacturing, engineering, service, administrative, and business related process problems.

Black Belts will be taught how to scope projects, define them and lead their implementation in addition to learning other essential skills including application of DMAIC, Six Sigma methodology for process improvement, as well as how to identify input variables that directly affect process output. Participants will work a Training Project within MindPro that will allow them to exercise all the tools taught during training as well as understand the methodology and steps needed to carry out an on-site organizational project.

Upon completion of Six Sigma Black Belt training, students will have the expertise and technical knowledge required to implement Six Sigma successfully and to propel their respective organizations toward best-in-class status by reducing costs, improving cycle times, eliminating defects and significantly increasing customer satisfaction. Total instructional time for this program is approximately 160 hours.


      Downloadable Program Syllabus

Training Orientation

Excel Orientation - Explore the Excel software package

Minitab Orientation - Explore the Minitab software package

Simulator Orientation - Explore the Process Simulator

Breakthrough Vision

Content Overview - Understand the nature, purpose, and drivers of Six Sigma

Instruction Videos
1. Basic Nature and Aims of Six Sigma -  3m 10s - 9.46 MB
2. Organizational Perspectives of Six Sigma -  6m 35s - 19.66 MB
3. Underlying Mechanics of Six Sigma -  3m 17s - 9.80 MB
4. Focused Use and Application of Six Sigma -  5m 48s - 17.30 MB
5. Deployment Roles Commonly Associated With Six Sigma -  3m 23s - 10.15 MB
6. Six Sigma Roles and Business-Focused Projects -  4m 07s - 12.32 MB
7. Analytical Tools Related to the Practice of Six Sigma -  3m 55s - 11.70 MB
Expansion Videos
8. Nature and Purpose of Big Ideas -  0m 52s - 0.52 MB
9. Concept and Implications of Process Control -  7m 26s - 7.58 MB
10. Concept and Implications of Process Capability -  6m 25s - 6.96 MB
11. Concept and Implications of Process Centering -  7m 32s - 6.70 MB
Application Videos
12. Key Ideas and Concepts Underpinning Six Sigma -  5m 50s - 3.07 MB
13. Connections between Quality Concepts and Six Sigma -  6m 06s - 4.02 MB
14. Connections between Six Sigma and Process Variation -  7m 14s - 6.63 MB
15. Basic Application of Six Sigma Concepts - Part A -  7m 43s - 11.48 MB
16. Basic Application of Six Sigma Concepts - Part B -  7m 20s - 5.45 MB
17. Basic Concepts of Design-for-Six-Sigma (DFSS) -  1m 58s - 2.31 MB
18. Critical Links between Six Sigma and Process Yield - Part A -  5m 10s - 2.91 MB
19. Critical Links between Six Sigma and Process Yield - Part B -  8m 33s - 6.39 MB
20. Critical Links between Yield and Complexity - Part A -  6m 56s - 3.82 MB
21. Critical Links between Yield and Complexity - Part B -  7m 27s - 4.87 MB
22. Critical Links between Yield and Complexity - Part C -  7m 00s - 14.10 MB
23. Proven Strategies for Realizing Breakthrough -  5m 19s - 4.92 MB
Supporting Media
Summary Slides: Content Overview

Driving Need - Identify the needs that underlie a Six Sigma initiative

Customer Focus - Explain why focusing on the customer is essential to business success

Core Beliefs - Contrast the core beliefs of Six Sigma to conventional practices

Deterministic Reasoning - Describe a basic cause-and-effect relationship in terms of Y=f(X)

Leverage Principle - Relate the principle of leverage to an improvement project

Tool Selection - Identify the primary family of analytical tools used in Six Sigma work

Performance Breakthrough - Describe the underlying logic of the DMAIC improvement process

Business Principles

Quality Definition - Articulate the idea of quality in terms of value entitlement

Value Proposition - Define the primary components of value and their key elements

Metrics Reporting - Recognize the need for installing and reporting performance metrics

BOPI Goals - Recognize the need for cascading performance metrics

Underpinning Economics - Describe the relationship between quality and cost

Third Generation - Differentiate between the first, second and third generations of Six Sigma

Success Factors - Identify the primary success factors related to a Six Sigma deployment

Instruction Videos
1. Maintaining a Customer Focus to Ensure Improvement -  5m 22s - 5.44 MB
2. Understanding the Need for Executive Leadership -  3m 26s - 3.52 MB
3. Building the Momentum toward Breakthrough -  5m 42s - 5.78 MB
4. Grasping the Power of Committed Resources -  4m 33s - 4.62 MB
5. Developing a Six Sigma Knowledge Infrastructure -  6m 17s - 6.38 MB
6. Creating and Managing Six Sigma Support Systems -  6m 12s - 6.29 MB
7. Understanding the Dynamic Force of a Collective Will -  3m 16s - 3.35 MB
8. Focusing Application Projects on Business Goals -  8m 08s - 8.26 MB
9. Developing Highly Capable People and Leaders -  3m 27s - 3.49 MB
10. Motivating the Creation of Compelling Ideas -  4m 37s - 4.68 MB
11. Basic Principles of Six Sigma Deployment Planning -  5m 14s - 5.31 MB
12. Questing for the Realization of Operational Freedom -  5m 10s - 5.24 MB
Expansion Videos
13. Understanding the Power of Six Sigma Tactics and Tools -  2m 20s - 1.01 MB
14. General Electric Six Sigma Case Study -  3m 49s - 1.97 MB
15. Dow Chemical Six Sigma Case Study -  6m 03s - 3.84 MB
16. DuPont Six Sigma Case Study -  3m 02s - 4.19 MB
17. Deeper Look into General Electric -  3m 57s - 8.60 MB
18. Fort Wayne Government Applications of Six Sigma -  6m 40s - 3.85 MB
19. Fort Wayne Water Main Case Study -  3m 10s - 1.61 MB
20. Fort Wayne Transportation Project Case Study -  1m 25s - 0.70 MB
21. Fort Wayne Site Plan Routing Case Study -  1m 21s - 0.64 MB
22. Fort Wayne Water Treatment Plant Case Study -  2m 37s - 1.66 MB
23. Fort Wayne Fire Code Inspection Case Study -  2m 22s - 1.24 MB
24. Fort Wayne Job Fulfillment Case Study -  2m 31s - 1.66 MB
25. Fort Wayne Garbage Pick-up Case Study -  2m 25s - 1.12 MB
26. Fort Wayne Pot-Hole Repair Case Study -  3m 23s - 1.75 MB
27. Fort Wayne Job Safety Case Study -  3m 50s - 1.95 MB
28. Fort Wayne Law Enforcement Case Study -  3m 04s - 1.63 MB
Supporting Media
Summary Slides: Success Factors

Process Management

Performance Yield - Explain why final yield is often higher than first-time yield

Hidden Processes - Describe the non-value added component of a process

Measurement Power - Describe the role of measurement in an improvement initiative

Establishing Baselines - Explain why performance baselines are essential to realizing improvement

Performance Benchmarks - Explain how a benchmarking chart can be used to assess quality performance

Defect Opportunity - Understand the nature of a defect opportunity and its role in metrics reporting

Process Models - Define the key features of a Six Sigma performance model

Process Capability - Identify the primary indices of process capability

Design Complexity - Describe the impact of complexity on product and service quality

Product Reliability - Explain how process capability can impact product reliability

Installation Guidelines

Deployment Planning - Understand the elements of Deployment Planning

Deployment Timeline - Understand the elements of a Deployment Timeline

CXO Role - Receive insight on how key decisions are addressed

Champion Role - Define the operational role of a Six Sigma Champion and highlight key attributes

Black Belt Role - Define the operational role of a Six Sigma Black Belt and highlight key attributes

Green Belt Role - Define the operational role of a Six Sigma Green Belt and highlight key attributes

White Belt Role - Define the operational role of a Six Sigma White Belt and highlight key attributes

Application Projects - Describe the purpose of Six Sigma Application Projects and how such projects are executed

DFSS Principles - See how product design can affect yield and performance

PFSS Principles - Have an understanding of the Process For Six Sigma Criteria

MFSS Principles - Understand how Managing For Six Sigma works

Application Projects

Project Description - Understand how to fully define a Six Sigma application project

Project Overview - Provide an overview of the key elements that characterizes an application project

Project Guidelines - Explain how to establish project selection guidelines

Project Scope - Explain how to properly scope an application project

Project Leadership - Recognize the actions that must occur to ensure successful project leadership

Project Teams - Form a project team that is capable of supporting Six Sigma applications

Project Financials - Understand the role of project financials in supporting deployment success

Project Management - Explain how application projects are best managed to achieve maximum results

Project Payback - Understand the driving need for establishing project paybacks

Project Milestones - Identify the primary milestones associated with a successful Six Sigma deployment

Project Charters - Understand the role of project charters and how they are used to guide implementation

Value Focus

Value Creation - Define the idea of value and explain how it can be created

Recognize Needs - Recognize the power of need fulfillment and how it links to value creation

Define Opportunities - Understand how to define opportunities that lead to the creation of value

Measure Conditions - Identify and evaluate the conditions that underlies improvement opportunity

Analyze Forces - Explain how the underlying forces are identified and leveraged to create beneficial change

Improve Settings - Establish optimal settings for each of the key forces that underpins beneficial change

Control Variations - Discuss how unwanted variations can mask the pathway to breakthrough

Standardize Factors - Understand the role and importance of standardized success factors

Integrate Lessons - Explain how key lessons learned can be merged into a set of best practices

Application Example - Understand how the breakthrough process can be applied to everyday life

Lean Practices

Lean Thinking - Comprehend the underlying logic of lean thinking

Constraint Theory - Explain how constraint theory is related to value creation

Continuous Flow - Describe the operational ideas that underpins continuous flow

Pull Systems - Contrast the operation of a push system to that of a pull system

Visual Factory - Explain the role of a visual factory during improvement efforts

Kanban System - Describe how a Kanban system can improve process cycle-time

PokaYoke System - Understand how PokaYoke systems can lead to quality improvement

6S System - Explain how the 6S system can contribute to process efficiency

SMED System - Define the basic elements of an SMED system

7W Approach - Describe how the 7W approach can be used to solve problems

6M Approach - Explain how the 6M approach is used to identify sources of causation

Quality Tools

Variable Classifications - Define the various types of variables commonly encountered during quality improvement

Measurement Scales - Describe each of the four primary scales of measure and their relative power

Problem Definition - Characterize the nature of a sound problem statement

Focused Brainstorming - Explain how focused brainstorming is used to facilitate improvement efforts

Process Mapping - Understand how to define the flow of a process and map its operations

SIPOC Diagram - Describe the nature and purpose of an SIPOC diagram

Force-Field Analysis - Utilize force field analysis to solve problems

Matrix Analysis - Understand how matrices are created and used to facilitate problem solving

C&E Analysis - Explain how C&E matrices can be used to solve quality problems

Failure Mode Analysis - Understand how FMEA is used to realize process and design improvements

Performance Sampling - Explain how to design and implement a sampling plan

Check Sheets - Understand how check sheets can be used for purposes of data collection

Analytical Charts - Identify the general range of analytical charts that can be used to assess performance

Pareto Charts - Explain how Pareto charts can be used to isolate improvement leverage

Run Charts - Utilize run charts to assess and characterize time-based process data

Multi-Vari Charts - Define the major families of variation and how they can be graphed

Correlation Charts - Utilize a correlation chart to illustrate the association between two variables

Frequency Tables - Explain how to construct and interpret a frequency table

Performance Histograms - Construct and interpret a histogram and describe several purposes

Basic Probability - Understand basic probability theory and how it relates to process improvement

Pre-Control Charts - Describe the fundamental rules that guide the operation of a standard pre-control plan

Control Charts - Explain the purpose of statistical process control charts and the logic of their operation

Score Cards - Understand the purpose of Six Sigma score cards and how they are deployed

Search Patterns - Explain how the use of designed experiments can facilitate problem solving

Concept Integration - Understand how to sequence a given selection of quality tools to better solve problems

Quality Simulation - Employ the related quality tools to analyze data generated by the process simulator

Basic Statistics

Performance Variables - Identify and describe the types of variables typically encountered in field work

Statistical Notation - Recognize and interpret the conventional forms of statistical notation

Performance Variation - Explain the basic nature of variation and how it can adversely impact quality

Normal Distribution - Describe the features and properties that are characteristic of a normal distribution

Distribution Analysis - Explain how to test the assumption that a set of data is normally distributed

Location Indices - Identify, compute, and interpret the mean, median, and mode

Dispersion Indices - Identify, compute, and interpret the range, variance, and standard deviation

Quadratic Deviations - Understand the nature of a quadratic deviation and its basic purpose

Variation Coefficient - Compute and interpret the coefficient of variation

Deviation Freedom - Explain the concept of degrees-of-freedom and how it is used in statistical work

Standard Transform - Describe how to transform a set of raw data into standard normal deviates

Standard Z-Probability - Describe how to convert a standard normal deviate into its corresponding probability

Central Limit - Understand that the distribution of sampling averages follows a normal distribution

Standard Error - Recognize that the dispersion of sampling averages is described by the standard error

Student's Distribution - Understand that the T distribution applies when sampling is less than infinite

Standard T-Probability - Describe how to convert a T value into its corresponding probability

Statistics Simulation - Employ basic statistics to analyze data generated by the process simulator

Continuous Capability

Performance Specifications - Explain the basic nature and purpose of performance specification limits

Rational Subgrouping - Explain how to form rational subgroups and describe their purpose in Six Sigma work

Capability Study - Understand the concept of process capability and how it applies to products and services

Instantaneous Capability - Understand the concept of instantaneous capability in relation to Six Sigma work

Longitudinal Capability - Understand the concept of longitudinal capability in relation to Six Sigma work

Cp Index - Compute and interpret Cp

Cpk Index - Compute and interpret Cpk

Pp Index - Compute and interpret Pp

Ppk Index - Compute and interpret Ppk

Process Shifting - Understand the impact of process centering error on short-term capability

Process Qualification - Determine the required level of short-term capability necessary to qualify a process

Instruction Videos
1. Nature and Purpose of Process Qualification - Part A -  2m 09s - 2.21 MB
2. Nature and Purpose of Process Qualification - Part B -  1m 45s - 1.79 MB
3. Elements of a Process Qualification Study - Part A -  2m 40s - 2.73 MB
4. Elements of a Process Qualification Study - Part B -  5m 52s - 5.95 MB
5. Elements of a Process Qualification Study - Part C -  3m 54s - 3.99 MB
6. Elements of a Process Qualification Study - Part D -  3m 27s - 3.53 MB
7. Linking Statistics to Process Qualification - Part A -  4m 56s - 5.02 MB
8. Linking Statistics to Process Qualification - Part B -  5m 28s - 5.54 MB
Expansion Videos
9. Six Sigma Models and Process Qualification - Part A -  6m 34s - 3.32 MB
10. Six Sigma Models and Process Qualification - Part B -  8m 09s - 7.96 MB
11. Six Sigma Models and Process Qualification - Part C -  4m 29s - 2.49 MB
12. Six Sigma Models and Process Qualification - Part D -  9m 33s - 8.33 MB
13. Six Sigma Models and Process Qualification - Part E -  11m 04s - 7.16 MB
Application Videos
14. Calculation of Process Qualification Statistics - Part A -  3m 03s - 1.45 MB
15. Calculation of Process Qualification Statistics - Part B -  3m 58s - 2.35 MB
16. Calculation of Process Qualification Statistics - Part C -  4m 11s - 2.50 MB
17. Calculation of Process Qualification Statistics - Part D -  4m 51s - 2.41 MB
18. Simulation of Process Qualification Statistics - Part A -  7m 17s - 8.82 MB
19. Simulation of Process Qualification Statistics - Part B -  6m 00s - 5.09 MB
Supporting Media
Summary Slides: Process Qualification

ConcaP Simulation - Apply continuous indices of capability to the process simulator

Discrete Capability

Defect Metrics - Identify and describe the defect metrics commonly used in Six Sigma work

Defect Opportunities - Understand the nature and purpose of defect opportunities in terms of quality reporting

Binomial Distribution - Describe the features and properties that are characteristic of a binomial distribution

Poisson Distribution - Describe the features and properties that are characteristic of the Poisson distribution

Throughput Yield - Compute and interpret throughput yield in the context of Six Sigma work

Rolled Yield - Compute and interpret rolled-throughput yield in the context of Six Sigma work

Metrics Conversion - Convert yield and defect metrics to the sigma scale of measure

Instruction Videos
1. Practical Need for Converting Performance Metrics -  6m 43s - 6.36 MB
Application Videos
2. Case of Zero Defects and Sigma Values - Part A -  4m 25s - 5.24 MB
3. Case of Zero Defects and Sigma Values - Part B -  6m 27s - 7.07 MB
4. First-Order Conversion of Performance Metrics - Part A -  3m 16s - 3.91 MB
5. First-Order Conversion of Performance Metrics - Part B -  3m 06s - 3.21 MB
6. First-Order Conversion of Performance Metrics - Part C -  3m 44s - 4.85 MB
7. First-Order Conversion of Performance Metrics - Part D -  5m 29s - 6.16 MB
8. First-Order Conversion of Performance Metrics - Part E -  1m 41s - 2.06 MB
9. First-Order Conversion of Performance Metrics - Part F -  3m 52s - 4.23 MB
10. First-Order Conversion of Performance Metrics - Part G -  5m 17s - 5.86 MB
11. First-Order Conversion of Performance Metrics - Part H -  3m 35s - 4.33 MB
12. First-Order Conversion of Performance Metrics - Part I -  2m 28s - 3.43 MB
13. First-Order Conversion of Performance Metrics - Part J -  2m 49s - 3.85 MB
14. First-Order Conversion of Performance Metrics - Part K -  2m 57s - 4.03 MB
15. First-Order Conversion of Performance Metrics - Part L -  5m 44s - 7.71 MB
16. First-Order Conversion of Performance Metrics - Part M -  3m 03s - 4.00 MB
17. First-Order Conversion of Performance Metrics - Part N -  1m 26s - 1.79 MB
18. First-Order Conversion of Performance Metrics - Part O -  2m 20s - 2.78 MB
19. First-Order Conversion of Performance Metrics - Part P -  5m 29s - 7.11 MB
20. First-Order Conversion of Performance Metrics - Part Q -  5m 48s - 7.61 MB
21. First-Order Conversion of Performance Metrics - Part R -  3m 38s - 5.11 MB
22. First-Order Conversion of Performance Metrics - Part S -  4m 12s - 3.88 MB
23. First-Order Conversion of Performance Metrics - Part T -  4m 50s - 5.79 MB
Supporting Media
Summary Slides: Metrics Conversion

DiscaP Simulation - Apply discrete indices of capability to the process simulator

Hypothesis Testing

Statistical Inferences - Explain the concept of a statistical inference and its primary benefits

Statistical Questions - Explain the nature and purpose of a statistical question

Statistical Problems - Understand why practical problems must be translated into statistical problems

Null Hypotheses - Define the nature and role of null hypotheses when making process improvements

Alternate Hypotheses - Define the nature and role of alternate hypotheses when making process improvements

Statistical Significance - Explain the concept of statistical significance versus practical significance

Alpha Risk - Explain the concept of alpha risk in terms of the alternate hypothesis

Beta Risk - Define the meaning of beta risk and how it relates to test sensitivity

Criterion Differences - Explain the role of a criterion difference when testing hypotheses

Decision Scenarios - Develop a scenario that exemplifies the use of hypothesis testing

Sample Size - Define the statistical elements that must be considered when computing sample size

Instruction Videos
1. Nature and Implications of Sample Size - Part A -  3m 50s - 3.89 MB
2. Nature and Implications of Sample Size - Part B -  3m 58s - 4.06 MB
3. Determination of Sample Size for Experiments - Part A -  7m 00s - 7.12 MB
4. Determination of Sample Size for Experiments - Part B -  8m 13s - 8.35 MB
5. Key Considerations for Computing Sample Size -  9m 41s - 9.85 MB
6. Calculation of an Appropriate Sample Size - Part A -  5m 14s - 5.32 MB
7. Calculation of an Appropriate Sample Size - Part B -  3m 15s - 3.32 MB
8. Calculation of an Appropriate Sample Size - Part C -  5m 26s - 5.51 MB
9. Calculation of an Appropriate Sample Size - Part D -  7m 42s - 7.85 MB
10. Calculation of an Appropriate Sample Size - Part E -  6m 12s - 6.29 MB
11. Relationship between Six Sigma and Sample Size -  9m 29s - 9.64 MB
12. Role of Sample Size in Hypothesis Testing - Part A -  5m 46s - 5.85 MB
13. Role of Sample Size in Hypothesis Testing - Part B -  7m 41s - 7.81 MB
Application Videos
14. Example Calculation of Sample Size - Part A -  6m 34s - 3.04 MB
15. Example Calculation of Sample Size - Part B -  3m 38s - 1.84 MB
16. Calculation of Sample Size for Discrete Data - Part A -  3m 57s - 4.10 MB
17. Calculation of Sample Size for Discrete Data - Part B -  2m 49s - 2.81 MB
18. Power of a Test and Random Sampling - Part A -  4m 48s - 4.35 MB
19. Power of a Test and Random Sampling - Part B -  1m 41s - 1.90 MB
20. Power of a Test and Random Sampling - Part C -  3m 03s - 3.59 MB
Supporting Media
Summary Slides: Sample Size

Confidence Intervals

Mean Distribution - Comprehend and characterize the distribution of sampling averages

Mean Interval - Compute and interpret the confidence interval of a mean

Variance Distribution - Comprehend and characterize the distribution of sampling variances

Variance Interval - Compute and interpret the confidence interval of a variance

Proportion Distribution - Comprehend and characterize the distribution of sampling proportions

Proportion Interval - Compute and interpret the confidence interval of a proportion

Frequency Interval - Describe how frequency of defects is related to confidence intervals

Control Methods

Statistical Control - Explain the meaning of statistical control in terms of random variation

Control Logic - Explain the logic that underpins the application of a control chart

Control Limits - Reconcile the difference between specification limits and control limits

Chart Selection - Explain how to rationally select a control chart

Chart Interpretation - Interpret an SPC chart in terms of its control limits

Zone Testing - Explain the concept of zone tests and their application to SPC charts

Variables Chart - Characterize the role and purpose of a variables chart

Attribute Chart - Characterize the role and purpose of an attribute chart

Individuals Chart - Construct and interpret an individuals control chart

IMR Chart - Construct and interpret an individual moving range control chart

Xbar Chart - Construct and interpret a control chart for subgroup averages

Range Chart - Construct and interpret a control chart for subgroup ranges

Proportion Chart - Construct and interpret a control chart for sampling proportions

Defect Chart - Construct and interpret a control chart for defect occurrences

Other Charts - Describe several other types of control charts used in Six Sigma work

Capability Studies - Explain the role of capability studies when making process improvements

Control Simulation - Apply common SPC methods to the process simulator

Parametric Methods

Mean Differences - Determine if two means are statistically different from each other

Variance Differences - Determine if two variances are statistically different from each other

Variation Total - Compute and interpret the total sums-of-squares

Variation Within - Compute and interpret the within-group sums-of-squares

Variation Between - Compute and interpret the between-group sums-of-squares

Variation Analysis - Explain how the analysis of variances can reveal mean differences

One-Way ANOVA - Construct and interpret a one-way analysis-of-variance table

Two-Way ANOVA - Construct and interpret a two-way analysis-of-variance table

N-Way ANOVA - Construct and interpret an N-way analysis-of-variance table

ANOVA Graphs - Construct and interpret a main effects plot as well as an interaction plot

Linear Regression - Conduct a linear regression and construct an appropriate model

Multiple Regression - Conduct a multiple regression and construct an appropriate model

Residual Analysis - Compute and analyze the residuals resulting from a simple regression

Parametric Simulation - Apply general regression methods to the process simulator

Chi-Square Methods

Statistical Definition - Describe how to translate a practical problem into a statistical problem

Model Fitting - Explain what is meant by the term "Model Fitting" and discuss its practical role in Six Sigma work

Testing Independence - Explain how a test of independence can be related to the idea of correlation

Contingency Coefficients - Understand how a contingency coefficient relates to a cross-tabulation table

Yates Correction - Describe the role of Yates correction in terms of the chi-square statistic

Testing Proportions - Test the significance of two proportions using the Chi-square statistic

Survey Methods

Research Design - Explain how the idea of research design fit with the idea of problem Solving

Information Sources - Explain how the idea of research design fit with the idea of problem Solving

Questionnaire Construction - Describe the role of survey demographics when analyzing closed-form survey data

Formulating Questions - Identify several things that should be avoided when developing survey questions

Question Quality - Explain what is meant by the term "question quality" and how this idea relates to data analysis

Sampling Plans - Describe several different types of sampling plans commonly used in survey research

Data Analysis - Explain how categorical survey data can be analyzed to establish strength of association

Nonparametric Methods

Nonparametric Concepts - Explain the difference between parametric and nonparametric methods

Median Test - Execute a median test on two groups and then determine if the difference is statistically significant

Runs Test - Conduct a runs test to determine if a time series pattern is random

Other Tests - Identify two nonparametric methods other than a median or runs test

Experimental Methods

Design Principles - Understand the principles of experiment design and analysis

Design Models - Describe the various types of designed experiments and their applications

Experimental Strategies - Outline a strategy for designing and analyzing a statistical experiment

Experimental Effects - Define the various types of experimental effects and how they impact decisions

One-Factor Two Level - Configure and analyze a one-factor two-level statistically based experiment

One-Factor Multi Level - Configure and analyze a one-factor multi-level statistically based experiment

Full Factorials - Understand the nature and underlying logic of full factorial experiments

Two-Factor Two Levels - Configure and analyze a two-factor two-level statistically based experiment

Instruction Videos
1. Two-Factor Two-Level Experiment Design - Part A -  4m 44s - 4.47 MB
2. Two-Factor Two-Level Experiment Design - Part B -  3m 29s - 3.29 MB
3. Two-Factor Two-Level Experiment Design - Part C -  2m 54s - 2.75 MB
4. Calculation and Display of Key Experimental Effects -  5m 04s - 4.78 MB
5. Graphing and Interpretation of Main Effects -  4m 33s - 4.30 MB
6. Graphing and Interpretation of Interactions - Part A -  4m 58s - 4.71 MB
7. Graphing and Interpretation of Interactions - Part B -  4m 46s - 4.50 MB
8. Creation and Structure of a Two-Way ANOVA Table -  8m 22s - 7.94 MB
9. Discovering the Path-of-Steepest-Assent - Part A -  8m 13s - 7.78 MB
10. Discovering the Path-of-Steepest-Assent - Part B -  5m 43s - 5.41 MB
Expansion Videos
11. Use of DOE to Facilitate Team Decision Making - Part A -  3m 26s - 1.39 MB
12. Use of DOE to Facilitate Team Decision Making - Part B -  6m 00s - 4.68 MB
13. Use of DOE to Facilitate Team Decision Making - Part C -  3m 28s - 1.54 MB
14. Use of DOE to Facilitate Team Decision Making - Part D -  5m 04s - 2.88 MB
15. Use of DOE to Facilitate Team Decision Making - Part E -  4m 24s - 2.30 MB
16. Use of DOE to Facilitate Team Decision Making - Part F -  3m 22s - 2.30 MB
17. Use of DOE to Facilitate Team Decision Making - Part G -  6m 01s - 2.99 MB
18. Use of DOE to Facilitate Team Decision Making - Part H -  2m 39s - 1.29 MB
Application Videos
19. Contrast Method for Conducting an ANOVA - Part A -  9m 33s - 10.82 MB
20. Contrast Method for Conducting an ANOVA - Part B -  2m 55s - 3.62 MB
21. Generation of a Two-Factor Two-Level Design - Part A -  6m 17s - 6.92 MB
22. Generation of a Two-Factor Two-Level Design - Part B -  2m 32s - 2.88 MB
23. Analysis of a Replicated Two-Factor Experiment -  7m 48s - 8.90 MB
24. Analysis of an Unreplicated Two-Factor Experiment -  5m 31s - 5.42 MB
25. Catapult Case Study for a Two-Factor Experiment -  11m 40s - 8.88 MB
Supporting Media
Summary Slides: Two-Factor Two Levels

Two-Factor Multi Level - Configure and analyze a two-factor multi-level statistically based experiment

Three-Factor Two Level - Configure and analyze a three-factor two-level statistically based experiment

Planning Experiments - Understand the planning and implementation considerations related to statistical experiments

Fractional Factorials - Understand the nature and underlying logic of fractional factorial experiments

Four-Factor Half-Fraction - Configure and analyze a four-factor half-fraction statistically based experiment

Five-Factor Half-Fraction - Configure and analyze a five-factor half-fraction statistically based experiment

Screening Designs - Understand how to select, implement, and analyze a screening experiment

Robust Designs - Explain the purpose of robust design and define several practical usages

Experiment Simulation - Describe how a DOE can be employed when measurement data is not available

DFSS Methods

QFD Method - Explain how quality function deployment can be used to help identify design specifications

Capability Flow-Down - Describe how a capability flow-down can be used as a risk allocation and abatement tool

Capability Flow-Up - Describe how a capability flow-up can be used to analyze the reproducibility of a design

Tolerance Analysis - Demonstrate how the RSS method can be used to analyze assembly tolerances

Instruction Videos
1. Calculations for Statistical Tolerance Analysis - Part A -  7m 22s - 7.50 MB
2. Calculations for Statistical Tolerance Analysis - Part B -  4m 37s - 4.70 MB
3. Calculations for Statistical Tolerance Analysis - Part C -  7m 33s - 7.68 MB
4. Basic Aims of Statistical Tolerance Optimization -  2m 19s - 2.37 MB
Application Videos
5. Short-Stack Tolerance Case Study and Analysis - Part A -  2m 26s - 1.08 MB
6. Short-Stack Tolerance Case Study and Analysis - Part B -  4m 08s - 3.61 MB
7. Short-Stack Tolerance Case Study and Analysis - Part C -  4m 15s - 3.93 MB
8. Short-Stack Tolerance Case Study and Analysis - Part D -  2m 26s - 2.28 MB
9. Short-Stack Tolerance Case Study and Analysis - Part E -  5m 20s - 3.30 MB
10. Short-Stack Tolerance Case Study and Analysis - Part F -  3m 40s - 2.02 MB
11. Short-Stack Tolerance Case Study and Analysis - Part G -  3m 04s - 1.69 MB
12. Finance Tolerance Case Study and Analysis- Part A -  2m 06s - 1.15 MB
13. Finance Tolerance Case Study and Analysis- Part B -  4m 29s - 4.73 MB
14. Finance Tolerance Case Study and Analysis- Part C -  4m 33s - 4.82 MB
15. Cycle Time Tolerancing Case Study and Analysis -  4m 59s - 3.87 MB
16. Widget Tolerancing Case Study and Analysis - Part A -  2m 21s - 1.45 MB
17. Widget Tolerancing Case Study and Analysis - Part B -  5m 10s - 3.12 MB
18. Widget Tolerancing Case Study and Analysis - Part C -  3m 04s - 1.95 MB
19. Widget Tolerancing Case Study and Analysis - Part D -  5m 49s - 4.72 MB
20. Widget Tolerancing Case Study and Analysis - Part E -  5m 37s - 4.26 MB
21. Widget Tolerancing Case Study and Analysis - Part F -  4m 44s - 4.66 MB
22. Widget Tolerancing Case Study and Analysis - Part G -  5m 03s - 4.56 MB
23. Widget Tolerancing Case Study and Analysis - Part H -  2m 51s - 2.20 MB
24. Widget Optimization and Allocation Case Study - Part A -  5m 49s - 4.43 MB
25. Widget Optimization and Allocation Case Study - Part B -  3m 36s - 4.42 MB
26. Widget Optimization and Allocation Case Study - Part C -  4m 34s - 2.10 MB
Supporting Media
Summary Slides: Tolerance Analysis

Monte-Carlo Simulation - Explain how Monte-Carlo simulation can be used during the process of design

Measurement Analysis

Measurement Uncertainty - Understand the concept of measurement uncertainty

Measurement Components - Describe the components of measurement error and their consequential impact

Measurement Studies - Explain how a measurement systems analysis is designed and conducted

Training Project

Project Introduction - Understand the steps to deploy a Training Project

Recognize Phase - Understand the tools used during the Recognize Phase

Define Phase - Execute the steps needed during the Define Phase

Measure Phase - Understand the tools needed during the Measure Phase

Analyze Phase - Become familiar with the tools used during the Analyze Phase

Improve Phase - Become familiar with the tools needed for improvement

Control Phase - Recognize the usage of tools needed for Process Control

Survey Analysis - Execute the techniques to analyze Survey data

Risk Analysis - Understand the tools needed for a Risk Analysis