Design of Experiments for Optimization

Experimentation plays an important role in science, technology, product design and formulation, commercialization, and process improvement. A well-designed experiment is essential once the results and conclusions that can be drawn from the experiment depend on the way the data is collected. This course will cover the basic concepts behind the Response Surface Methodology and Experimental Designs for maximizing or minimizing response variables.

Design of Experiments for Optimization course starts with a basic introduction to linear regression models and how to build regression models to fit experimental data and check the model adequacy. The next section covers experimental designs for linear models and the use of central points to check the model's linearity (lack-of-fit). By the end of the section, you will be using linear models to fit experiments with inaccurate levels in the design factors and missing observations. The whole learning process is illustrated with real examples from researchers in the industry and in the academy.

This course offers:

• Flexible deadlines: Reset deadlines based on your availability.
• Get a Certificate when you complete
• 100% online
• Intermediate level
• Approximately 1 hour to complete
• Subtitles: English

Participants: 550