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Program Description

Excel Orientation - Explore the Excel software package

Minitab Orientation - Explore the Minitab software package

Simulator Orientation - Explore the Process Simulator

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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