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)
