Six Sigma eLearning Glossary of Six Sigma Terms (A - D)

A - D

E - M

N -R

S - Z

The difference between the observed average value of the measurements and the true value.

Active Opportunities
Parts of the process or product that are specified and measured.

A synonym for confounding, in which one or more effects that cannot unambiguously be attributed to a single factor or interaction.

Alpha Risk
Producer’s Risk.  The probability of committing a Type I error – generally, the risk of incorrectly concluding that there is a difference.

Alternative Hypothesis
Statement of change or difference, such as a difference between the means of two samples.

Attribute Data 
Count data from membership in a category – such as “Good” or “Bad” parts.

A synonym for “mean”: the sum of a set of values divided by the number of values.

Balanced Design
An experiment
where each level of each factor is repeated the same number of times for the set of runs or combinations of levels that make up the experiment.

Bartlett’s Test
Test for equal variances, assuming normal data.

Beta Risk
Consumer’s Risk.  The probability of committing a Type II error – generally, the risk of incorrectly concluding that there is no difference.

Binomial Distribution
A distribution
usually used for determining confidence for proportions.  If there are two possible outcomes, such as either “pass” or “fail” for product tests, or either “heads” or “tails” for coin tosses, then the binomial distribution might be used to estimate the probability of 5 passes and 1 fail in 6 product tests or 2 heads and 2 tails in 4 coin tosses.

Black Belt
Experienced, recognized Six Sigma expert  and project leader, full-time quality position.

In a designed experiment, blocks can be used to handle uncontrolled factors that are generally considered “noises, having undesired influence as a source of variability. For example, a block can be used to handle humidity as an undesired “noise factor” that can influence the results but cannot be directly controlled by the experimenter.

An experimental design used in Response Surface Modeling to obtain polynomial equations with only three levels for each factor.

Business Process Management
The strategic component of Six Sigma methodology.

C- & u-charts
Control charts for defects.

Center Points
Runs in an experimental design at the midpoint of all of the quantitative factor levels.

Central Composite
An experimental design used in Response Surface Modeling design where star points and center points may be added to a factorial experiment, providing three or five levels for each factor.

Central Limit Theorem
A mathematically provable principle about obtaining means of samples that has two major ramifications:

- The standard deviation of averages of samples from the population will be approximately equal to the standard deviation of the population divided by the square root of the sample size.

- Regardless of the shape of the original distribution (even for very non-normal distributions such as exponential distributions), the distributions of averages of samples from the population approach the shape of a normal distribution.

Executive sponsor of quality initiative projects.

Chi-Square Distribution
A special case of a Gamma Distribution with one parameter that is used for determining confidence for standard deviations and in the Chi-Square test.

Chi-Square Test
A statistical test used to compare the difference between relative frequency of observed events to the frequency expected based on the assumption that is to be tested. 

Coefficient of Determination
R^2, the square of the correlation coefficient, which estimates the percent of the total variation in the response can be attributed to the variation of the input variables given a regression equation or model. It also is used to evaluate
the adequacy of a regression model.

Common Cause
Variation inherent to the design of the process.

Confidence Interval
A range describing where the true population parameter lies with a certain degree of confidence. For example, a 95% confidence interval for the mean estimates that the true mean lies within the confidence interval with 95% confidence (with 5% alpha risk).

One or more effects that cannot unambiguously be attributed to a single factor or interaction.

Continuous Data
Data from a measurement scale that can be divided into finer and finer increments. Examples of continuous data include time, temperature, and weight.

Contour Plot
A two-dimensional graph of three measurement variables: two inputs (x1 and x2) and one response (y), where contour lines connect points on the x1 and x2 plane that have the same value for y.

Control Limits
Natural process limits, determined from historical data of how the process will run if undisturbed. The control limits are at the historical mean or target +/- 3 x the historical standard deviation.

Control Plan
The summary of all the control actions for a process.

Correlation Coefficient
A statistic used for quantifying the strength of a linear association between variable inputs and outputs.  It ranges from +1 (perfect positive correlation: higher input goes with higher output) to -1 (perfect negative correlation: higher input goes with lower output).

The distance between the mean and the nearest specification limit divided by (3 x standard deviation).

Critical Difference
The practical change that the experimenter wants to have a high probability of detecting.

Critical Mass 
The number of people who become committed to Six Sigma that will then influence the organization to share the commitment.

When the output of the process does not seem to vary linearly with the input factor; with experimental designs, the output at the center point does not lie along a line between the output values at a low and at a high level of the input.  

Cyclical Variation
Piece to piece variation. Often used to describe a repeating pattern, such as a seasonal variation in sales that peaks before Christmas.

Decision Rules
The set of procedures for detecting and handling out of control conditions.

An output of a process that does not meet specification.

Products that have at least one defect.

Definition of a 6s Process 
Six standard deviations fit between the mean and the nearest specification limit.

Design Resolution
The worst case confounding scheme associated with a fractional factorial experimental design, conventionally described with Roman numerals. For example, a Design Resolution of IV indicates that main effects are confounded or mathematically indistinguishable from three-way interactions, and two-way interactions are confounded or mathematically indistinguishable from other two-way interactions.

Design For Six Sigma. (Also known as DMADV).

Define, Measure, Analyze, Design, Verify. (Also known as DFSS).

Define, Measure, Analyze, Improve, Control – Six Sigma process improvement method.

Design of Experiments, an efficient experimental strategy that allows the investigation of multiple factors at multiple levels.

DOE for Sigma
A designed experiment whose area of interest is reduction of variation.

Defects Per Million Opportunities, or 1 million times the Defects Per Unit divided by the opportunities for error per unit.

Defective Parts Per Million, or 1 million times the  Defective units/total units.

Total defects observed/total units produced.

Draftsman Plot
Plot for showing the two-variable relationships between a number of variables all at once by showing the projection of the response on three orthogonal surfaces of a cube

A gradual change in a process characteristic over time.

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