Section: Topic 6 | Design and Analysis of Experiments (2013) | phd moodle

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Section outline

Topic 6
Topics:

Graeco-Latin square designs.

Balanded incomplete block design.

Models and matrix algebra in linear regression.

Read: Montgomery, Sec. 4.3, 4.4 (stop before formula (4.28)), 10.1, 10.2, 10.3 (stop after formula (10.15) at p. 453, but do include Example 10.1 at p. 454-455).

Location: Fredrik Bajers Vej 7B, room B2-107

Remarks:

For BIBD, the crossing factors Treatment and Block are not orthogonal. Fortunately, R can do the calculations of Sum of Squares, such that the cumbersome formulae in the book are not needed. You can skip the calculations from Formula (4.28) and until the end of the section.

In this course, we assume that the response variable is quantitative (continuous). In analysis of variance (ANOVA), the explanatory variables are qualitative (factors), in regression analysis the explanatory variables are quantitative (continous), and in analysis of covariance (ANCOVA) there are both qualitative and quantitative explanatory variables.

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