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F ine Cuisine

F ine Cuisine. Mmmmmmmmmmmmm. Layout. Model. As Repeated Measures. Carcass is a Between Term All other terms in the Model are Within terms Error is non-retrievable in the full Model

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F ine Cuisine

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  1. Fine Cuisine Mmmmmmmmmmmmm

  2. Layout

  3. Model

  4. As Repeated Measures • Carcass is a Between Term • All other terms in the Model are Within terms • Error is non-retrievable in the full Model • Often Diagnostics are done by deleting the highest order Interaction and using residuals from this Reduced Model for Diagnostics (in particular it can be useful for finding problems with error variances)

  5. ANOVA Table

  6. Diagnostic Plot for Variances

  7. Residual Plots

  8. Normality Test

  9. ANOVA Table for Fixed Effects

  10. Interaction Plot

  11. Interaction Means HSD Comparisons

  12. Roasting Times Plot

  13. Tenderizer Means Plot

  14. What happens if Carcass (i.e. Unicorn) is left out of the Model?

  15. Subject variation went into Error • All tests are now against Error • F-statistics are different because of different error terms • Conclusions were not different for this data but they could have been.

  16. As a Split Plot • Tenderizer is Whole Plot Factor • Tenderizer*Carcass is the Whole Plot Error Term • Roasting Time and all Interactions with Roasting Time are Split Plot Terms • Roasting Time*Carcass and Tenderizer*Roasting_Time*Carcass are Split Plot Error Terms

  17. Design Question: Is it always true that…..

  18. Not always • In Agricultural field experiments it is typically true • In Industrial experiments where there is Batch to Batch variation, and Batches are nested within the Whole Plot Treatment, also true • Not necessarily true in Industrial experiments if there is really good Quality Control, i.e. if Batches are very consistent • Not necessarily true if Batch is crossed with the Whole Plot Treatment in Industry where Batches are very consistent • How to be sure? Look at the Mean Squares of the Error Terms

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