Planejamento e Otimização de Experimentos

Plano de Curso
Aulas Teóricas
- Parte I: Introdução
- Parte II: Estatística Básica
  - Rdata
- Parte III: Erros de Amostragem
- Parte IV: ANOVA
- Parte V: Blocking (randomized complete block, latin square, graeco-latin square, and randomized incomplete block designs)
- Parte VI: Full Factorial Design
- Parte VII: Fractional Factorial Design
- Parte VIII: planejamentos Plackett-Burman, 3k, mistos, nested e split-plot
- Parte IX: Response Surface Methodology
- Parte X: Mixture Designs
Aulas Práticas
- Learning R
  - swril (Learn R, in R and The Swirl Course Network)
  - DataCamp’s free R Tutorial
  - The 5 most effective ways to learn R
  - RStudio Education
- Estatística Básica
- Significance tests
- ANOVA
- Blocking
- (full) Factorial Design
  - R Tutorial
  - Full factorial example (NIST)
  - 2k design: páginas 14-21 e 29-36
  - In-class Examples with R: páginas 16-25
- Fractional Factorial Design
  - Reciple 8: the 2k factorial design
  - In-class Examples with R: páginas 26-35
- Additional Designs
  - Plackett-Burman
  - 3k
- Regression
  - ion analysis
  - multiple (linear) regression (Quick-R)
  - multiple regression (an R companion for the handbook of biological statistics)
  - multiple regression analysis in R - first steps
- Response Surface Methodology
  - CCD design
  - CCD and desirability
- Mixture Designs
  - Advanced Topics in Experimental Design (ex: Appendix A2)
  - Using an Experimental Mixture Design to Identify Experimental Regions with High Probability of Creating a Homogeneous Monolithic Column Capable of Flow

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