Exploring Best Practices in the Design of Experiments - JMP
Exploring Best Practices in the Design of Experiments - JMP
Exploring Best Practices in the Design of Experiments - JMP
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<strong>Design</strong> Properties<br />
1. The number <strong>of</strong> required runs is only one more<br />
than twice <strong>the</strong> number <strong>of</strong> factors.<br />
2. Unlike Plackett-Burman and Resolution III and IV<br />
fractional factorial designs, ma<strong>in</strong> effects are<br />
completely <strong>in</strong>dependent <strong>of</strong> two-factor<br />
<strong>in</strong>teractions.<br />
3. Unlike all predecessors, <strong>the</strong>se are three-level<br />
designs, so we can estimate curvatures!<br />
4. <strong>Design</strong>s are capable <strong>of</strong> estimat<strong>in</strong>g all possible<br />
full quadratic models <strong>in</strong>volv<strong>in</strong>g three or fewer<br />
factors with very high levels <strong>of</strong> statistical<br />
efficiency.<br />
4/29/2013<br />
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