Experimental Design and Industrial Statistics - III


The four-level sequence of courses in this series is intended to provide engineering, technical, and manufacturing personnel with an in-depth and working knowledge of industrial statistics and experimental design methods and techniques. Various aspects of this sequence combine to provide the most unique series of its type in the country, specifically:

  • There are no prerequisites to initiating the series, and the participants are assumed to enter the first course in the series with no prior knowledge of statistical theory;
  • The course sequence stresses applied versus theoretical methods and tools;
  • The course uses over 85 industrial examples and data sets to explore the tools and methods taught, all of which have been gathered in actual industrial applications; and
  • The course sequence is computer-based, to allow for the maximum amount of content to be covered, and ensures that participants will be capable of applying the knowledge and skills acquired in their own positions after the course sequence is successfully completed.

Participants completing the course sequence will be capable of properly gathering and analyzing data, as well as correctly designing and executing experiments in the industrial setting.

Time Requirement

10 days

Number of Participants

A maximum of 45 participants is recommended for this course sequence, with no more than two participants assigned to each computer.


Experimental Design and Industrial Statistics — Level II

Primary Resource Materials

Experimental Design and Industrial Statistics — Level III manual

Content Outline

Volume 1 — Planning and Conducting Designed Experiments in Industry


  • Introduction and Table of Contents
  • Identifying the Type and Purpose of the Research Study
  • Developing the Experimental Design
  • Designing the Industrial Experiment: Case Studies

Volume 2 — Planning and Conducting Designed Experiments in Industry

  • Sampling Procedures and Considerations
  • Establishing the Validity of the Data


  • Managing the Execution of the Experiment


  • Designing the Plan for the Statistical Analysis of the Data


  • Reporting the Results of the Research Study

Volume 3 — Advanced Statistical Methods

  • The Design and Analysis of a Randomized Comparative Experiment
  • The Design and Analysis of Factorial Experiments for 2 Factors
  • Two-Way ANOVA Models for Random and Mixed Effects
  • Disproportionate Frequency Analysis
  • Analysis of a Nested Factorial Design
  • The Design and Analysis of 2n Factorial Experiments
  • Testing for Homogeneity of Variance and Dispersion in Factorial Models
  • Simple and Multiple Regression Analysis
  • Response Surface Methodology


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