A. Measuring and modeling relationships
between variables
 Correlation
coefficient
Calculate and interpret the correlation coefficient
and its confidence
interval, and describe the difference
between correlation
and causation. (Analyze)
NOTE: Serial correlation will not be tested.
 Regression
Calculate and interpret regression
analysis, and apply and interpret
hypothesis
tests for regression statistics,.
Use the regression
model for estimation and prediction,
analyze the uncertainty of the estimate, and
perform a residuals
analysis to validate the model.
(Evaluate)
NOTE: Models that have nonlinear parameters
will not be tested.
 Multivariate
tools
Use and interpret multivariate tools such as
principal
components, factor
analysis, discriminant
analysis, multiple
analysis of variance (MANOVA),
etc., to investigate sources of variation. (Analyze)
 Multivari
studies
Use and interpret charts
of these studies and determine the
difference between positional,
cyclical
and temporal
variation. (Analyze)
 Attributes data analysis
Analyze attributes data using logit,
probit,
logistic
regression, etc., to investigate
sources of variation. (Analyze)
B. Hypothesis
Testing
 Terminology
Define and interpret the significance
level, power,
type
I and type
II errors of statistical tests.
(Evaluate)
 Statistical vs practical significance
Define, compare and interpret statistical
and practical significance. (Evaluate)
 Sample size
Calculate sample
size for common hypothesis
tests (e.g.,
equality
of means, equality
of proportions,
etc.) (Apply)
 Point and interval estimates
Define and distinguish between
confidence
and prediction
intervals. Define and interpret
the efficiency
and bias
of estimators. Calculate tolerance
and confidence intervals. (Evaluate)
 Tests for means, variances and proportions
Use and interpret the results of hypothesis
tests for means,
variances
and proportions.
(Evaluate)
 Analysis of Variance (ANOVA)
select, calculate and interpret the results
of ANOVAs.
(Evaluate)
 Goodnessoffit (chi
square) tests
Define, select and interpret the results of
these tests. (Evaluate)
 Contingency
tables
Select, develop and use contingency
tables to determine statistical
significance (Evaluate)
 Nonparametric
tests
Select, develop and use various nonparametric
tests including Mood's
Median, Levene's
test,
KruskalWallis, Mann
Whitney, etc. (Evaluate)
C. Failure
Mode and Effects Analysis (FMEA)
Describe the purpose and elements of FMEA, including
risk priority number (RPN),
and evaluate FMEA results for processes, products
and services. Distinguish between design
FMEA (DFMEA) and process
FMEA (PFMEA), and interpret results
from each. (Evaluate)
D. Additional analysis methods
 Gap analysis
Use various tools and techniques (gap
analysis, scenario
planning, etc.) to compare the
current and future state in terms of predefined
metrics. (Analyze)
 Root cause analysis
Define and describe the purpose of root
cause analysis, recognize the issues
involved in identifying a root cause, and use
various tools (e.g., the 5
whys,
Pareto charts,
fault
tree analysis, cause
and effect diagrams etc. for resolving
chronic problems. (Evaluate)
 Waste analysis
Identify and interpret the 7 classic wastes
(overproduction, inventory, defects, overprocessing,
waiting, motion and transportation) and other
forms of waste such as resources underutilization,
etc. (Analyze)
