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4. Models with Multiple Explanatory Variables

4. Models with Multiple Explanatory Variables. Chapter 2 assumed that the dependent variable (Y) is affected by only ONE explanatory variable (X). Sometimes this is the case. Example: Age = Days Alive/365.25 Usually , this is not the case. Example: midterm mark depends on:

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Completely Randomized Design

Completely Randomized Design. Cell means model:. Effects Model. GLM for Effects Model. CRD Contrasts. Balanced case (n i =n) -A linear combination L has the form: -A contrast is a linear combination with the additional constraint:. Cotton Fiber Example.

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4. Models with Multiple Explanatory Variables

Completely Randomized Design