Accuracy 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.
Aliasing 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.
Average 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 expertand project
leader, full-time quality position.
Block 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.
Box-Behnken 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.
Champion 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).
Confounding 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 measurementvariables:
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).
Cpk 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.
Curvature 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.
Defect An output of a
process that does not meet specification.
Defectives 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.
DFSS Design
For Six Sigma. (Also known as DMADV).
DMADV Define,
Measure, Analyze, Design, Verify. (Also known as DFSS).
DMAIC Define,
Measure, Analyze, Improve, Control – Six Sigma process improvement method.
DOE 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.
DPMO Defects Per
Million Opportunities, or 1 million times the Defects Per Unit divided by the
opportunities for error per unit.
DPPM Defective
Parts Per Million, or 1 million times theDefective units/total units.
DPU 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
Drift A gradual
change in a process characteristic over time.
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