MANE 6313
Week 5, Module D
Student Learning Outcome
Analyze simple comparative experiments and experiments with a single factor.
Module Learning Outcome
Evaluate Latin Square designs.
Latin Square Design
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Design that allows the elimination of two nuisance sources of variability.
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Each row and column represents a restriction on randomization (number of rows=number of columns=number of treatments)
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The statistical model is
\[
y_{ijk}=\mu+\alpha_i+\tau_j+\beta_k+\varepsilon_{ijk}\;\;\left\{\begin{array}{l}i=1,2,\ldots,p\\
j=1,2,\ldots,p\\ k=1,2,\ldots,p\end{array}\right.
\]
where \(\alpha_i\) is the \(i\)th row effect, \(\tau_j\) is the \(j\)th treatment effect, and \(\beta_k\) is the \(k\)th column effect
- ANOVA and SS formulas given on pg. 134.
Problem 4.28 (textbook, 9th edition)
Data Stored in Excel
Data Imported through readxl
Data Created using R
Analysis of Variance
Randomized Experiment
- Create with package agricolae
- Not recommended for homework problems but "real-world" usage
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Additional steps
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Create vector with response values
- Create create data frame containing response values and the design book
- Analysis with aov