Skip to content

MANE 6313

Week 11, Module A

Student Learning Outcome

  • Select an appropriate experimental design with one or more factors,
  • Select an appropriate model with one or more factors,
  • Evaluate statistical analyses of experimental designs,
  • Assess the model adequacy of any experimental design, and
  • Interpret model results.

Module Learning Outcome

Describe a general 2^(k-p) fractional factorial design.

The general \(2^{k-p}\) Fractional Factorial Design

  • A \(2^k\) fractional factorial design containing \(2^{k-p}\) runs is called a \(1/2^p\) fraction of the \(2^k\) design

  • These designs requires \(p\) independent generators (same definition from last week).

  • There are \(2^p-p-1\) generalized interactions included

  • There is an "art" to selecting the correct generators. Look to table 8.14 (page 353) for suggestions.

Resolution III Designs

  • It is possible to construct resolution III designs for investigating up to \(k=N-1\) factors in \(N\) runs when \(N\) is a multiple of 4

  • These experiments are said to be saturated

  • Pay particular attention to Sequential assembly of fractions to separate effects.

Problem 8_37 (Textbook 9th Edition)

Problem 8.37 Statement

Problem 8.37 Data Definition

Problem 8.37 Data

Design, part 1

Manual Design Matrix, part 1

Design, part 2

Manual Design Matrix, part 2

Defining Relation

Manual Aliasing Scheme