Principle Courses: These two courses provide the core statistical and software training needed for most industrial applications. The objective is to empower process and product engineers, scientists and middle managers, quality assurance professionals, and research scientists with tools for collecting, analyzing, and understanding data, variability, statistical significance, and risks for industrial decisions about processes, products and scientific phenomena. 

Great course! This really helped clear up some fog from my college stats class. STATGRAPHICS is really an impressive package.
A. R., R&D Engineer, Hewlett Packard

Industrial DOE (I-DOE): (with STATGRAPHICS Training and Application)
Design and Analysis of Experiments for Industrial Decisions

Specialty Courses: These courses offer specialty training (with STATGRAPHICS application) in two important areas for product, process and scientific investigations.

Reliability and Product Lifetime Analysis

• General Statistical Design and Analysis for Industrial Decisions: [Foundation course - 4 days] Basic statistics and STATGRAPHICS fundamentals. Framework for statistical thinking. Fitting distributions to data and estimating process yield. Estimation and testing. Statistical tolerance limits. Non-parametric and other methods when normality assumptions fail. Analyzing sources of variation, quantitative and qualitative variables and relationships between them. Benchmarking, process improvement, process comparisons, product/process validation decisions. 
• Optional 5th day: Process management, SPC, control charts, process capability analysis, gage R&R.

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Prerequisite: Exposure to working with data (equivalent to our Elementary Statistics course). Prior college statistics course helpful but not required.  top

• Design and Analysis of Industrial Experiments (DOE): [Focus course - 4 days] Review of framework for statistical thinking (with DOE Focus) and STATGRAPHICS. Experimental design principles, concepts and strategies. Simple comparisons, randomized and paired. Comparing several treatments/processes with multiple comparison procedures. Designs and analysis for process/product characterization. Designs and analysis for process/product optimization. Designs and analysis for measurement assurance.
• Optional 5th day: Advanced DOE, expected mean squares, general linear model, mixed models (fixed and random effects), nested-factorial designs, constraints on randomization.

 View syllabus

Prerequisite: Foundation course or instructor consent.  top

• Empirical Model Building for Industrial Decisions: [Focus course - 4 days] Review of framework for statistical thinking (with empirical modeling focus) and STATGRAPHICS. Exploratory data analysis. Multiple linear regression. Nonlinear regression. General linear model. Time series analysis and forecasting. Basic multivariate models and analysis techniques. View syllabus

Prerequisite: Foundation course or instructor consent.  top

• Reliability and Product Lifetime Analysis: [Focus course - 4 days] Review of framework for statistical thinking (with reliability focus) and STATGRAPHICS. Statistical models for life data. Probability plotting and other model-selection procedures. Survival and hazard functions. Estimation and hypothesis testing with Types I and II censoring. Design and analysis of accelerated life tests. Burn-in procedures. Non-parametric methods, Kaplan-Meier estimation, Cox regression model, log-rank test. View syllabus

Prerequisite: Foundation course or instructor consent.  top