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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

  • Design that allows the elimination of two nuisance sources of variability.

  • Each row and column represents a restriction on randomization (number of rows=number of columns=number of treatments)

  • 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 in Excel


Data Imported through readxl

Data imported through readxl


Data Created using R

Data Created using R


Analysis of Variance

Analysis of Variance


Randomized Experiment

  • Create with package agricolae
  • Not recommended for homework problems but "real-world" usage
  • Additional steps

  • Create vector with response values

  • Create create data frame containing response values and the design book
  • Analysis with aov

Randomized Experiment, continued

Graeco Latin Square Design - agricolae


R Demonstration