Full Factorial Experiments Explained

The full factorial is perhaps the most widely used statistically designed experiment, and allows teasing out complex interactions between different factors. However, it has its drawbacks, and we explore these as well.
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This is part of my playlist on Design of Experimens, the methodology for rigorous statistical design of experiments, with applications ranging from chemical process optimization to biology to crop yields and optimization of neural networks.

[@MisterBinx]

Great refresher. I passed design of experiments but would like to take the course again. These are powerful tools in engineering.

[@rizkyerzaldilaga471]

Hi! Do you mind sharing the course? I am keen to take this course.

[@victorlegrand7189]

@@rizkyerzaldilaga471 can share you if you want give me your email adress

[@Gabrielle-zi8go]

Thank you! This is very clear to understand and I like the way you draw roses lol

[@chiemelieumeh9013]

Thank you ,this has helped me prepare for my exam

[@CADable]

Great Explanation Professor❤

[@yasamanroudaki1730]

Perfect explanation!

[@Unik_anik]

Thanks

[@paolo7206]

OFAT en Full Factorial seem to have the SAME number of measurements. If you want to reduce then choose Fractional Factorial design?