Design of Experiments for Method Validation & Laboratory Studies

This course covers the design of experiments (DOE) and analysis of laboratory generated data. Laboratory applications of DOE include Measurement System Analysis (MSA), designed studies used in method validation and improvement, verification of competency, and evaluations of components of measurement uncertainty. The participant will learn the basic tools and potential pitfalls of experimental design and analysis of variance (ANOVA) by studying laboratory examples.

This virtual instructor-led course will be conducted online. On the right side of the page you will see the dates and times available for this course, each with an individual registration link. Learners will attend using a virtual learning program and will participate in live discussion and activities. A webcam and microphone are required. Details about how to log into the virtual learning program will be provided after your registration is complete.

Prerequisites

Intermediate Statistics for Laboratory Professionals (EMU 200) or equivalent knowledge.

Target Attendees

Target learners include Laboratory Managers, Engineers, Scientists, or Technicians.

Learning Outcomes

After successful competition of this course, the participant will be able to:

1. Explain the difference between discrete and continuous variables, and dependent and independent variables;
2. Develop a DOE plan to meet specific objectives;
3. Describe and apply randomization and blocking;
4. Set-up and interpret outcomes of Measurement System Analysis (MSA);
5. Interpret outputs of DOE analysis; and
6. Apply DOE to Method Validation, improvement and components of measurement uncertainty

LEUs Awarded

1.4 LEUs Awarded*

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