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DESIGN OF EXPERIMENTS (2. Unstructured Experiments (2.8 Sums of squares, 2…
DESIGN OF EXPERIMENTS
2. Unstructured Experiments
2.8 Sums of squares
2.9 Variance
2.7 Estimation
2.10 Replication: equal or unequal
2.6 The treatment subspace
2.11 Allowing for the overall mean
2.5 Some general results for linear models
2.12 Hypothesis testing
2.13 Sufficient replication for power
2.14 A more general model
2.1 Completely randomised designs
2.2 How and why to randomise
2.3 Some revision from MTH6134
2.4 Orthogonal projection
3. Blocking
3.4 Analysis: model with fixed block effects
3.3 Construction and randomisation
3.5 Analysis: model with random block effects
3.2 Orthogonal block designs
3.6 Why use blocks?
3.1 Types of block
3.1.2 Continuous gradients
3.1.3 Choice of blocking for trial management
3.1.1 Natural discrete divisions
4. Row-Column Designs
4.3 Construction and randomisation
4.4 Orthogonal subspaces
4.2 Latin squares
4.5 Fixed effects: model and analysis
4.1 Double blocking
4.6 Random effects: model and analysis
5. Factorial Treatment Structure
5.3 Interaction
5.4 Decomposing the treatment subspace
5.2 Treatment factors and their subspaces
5.5 Analysis
5.1 An example from MTH6134
1. Introduction
1.2 The ideal and the reality
1.3 Defining terms
1.1 Stages of a designed experiment
1.4 Linear model