Programação
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We will use this environment for interaction, questioning and solving weekly activities. I wish you a great semester!
Profa. Michele.
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Olá pessoal! Por favor, apresentem-se. Mencione sua instituição de origem, posição atual, etc. Explicite os motivos que o fez cursar a disciplina.
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Resolution of exercises 1-10.
Rencher, A. Linear Models in Statistics. 5–61 (1999). Chapter 2 - Matrix Algebra.
#Resolution of exercises 1-5, class 01a.
Deadline: August 30th.
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Practice the "Exercises02" in R.
Deadline: September 13th
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Read the paper "The fickle P value generates irreproducible results" (Halsey, 2015) and make a critical comment about the p-value and its importance.
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Practice the "Exercise04" in R.
Deadline: September 30th
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- Let y_ijk the severity of Fusarium of the ith wheat genotype, infected by the jth Fusarium strain, in year k
Deadline: October 6th- Use the R function read.csv to import the data
- Which models can we fit? (Tranditional and Mixed Models)
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- We will work with yield data of 17 rice genotypes, measured in three replications each (Data_rice)
#Use the R function read.csv to import the data#Fit the model with fixed effects#Use lm( ) function and summary( )#Check if model assumptions are met#Check raw residuals vs fitted values#Build the ANOVA table and test the null hypothesis of no difference between the rice genotypes#Use multiple pairwise comparisons to assess which genotypes differ#Fit the model with random effects#Deadline: October 20th
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#Load the "agridat" package
#Choose the dataset "federer.tobacco" from the agridat package
#Perform an analysis of variance (ANOVA) for the RCDB
#Tukey test for multiple comparisons of treatments
#Deadline: October 20th
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#Data: aspergillus.csv
#Use the R function read.csv to import the data#Fit the model with fixed (and/or random) effects#Check if model assumptions are met#Build the ANOVA table and test the null hypotheses of no difference between strains, no difference between nicotinic acid treatments and no interaction between both factors#Draw the interaction plot#Use multiple comparisons to assess pairwise differences#Deadline: November 08th -
Data: sunflower.csv
#Use the R function read.csv to import the data#Fit the model with fixed (and/or random) effects#Check if model assumptions are met#Build the ANOVA table and test the null hypothesis of no difference between genotypes
#Use multiple comparisons to assess pairwise differences
#Deadline: November 08th
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- The next data set contains colony diameter measurements (in mm) of ten strains of Aspergillus nidulans, at three incubation time points (48, 72 and 96 hours)-The ten strains were evaluated in a CRD with two replications- Each replicate of each strain was divided into three subplots, which were assigned the varying time treatments- Use the R function read.csv to import the data- Fit the model with fixed (and/or random) effects- Check if model assumptions are met- Build the ANOVA table and test the null hypotheses of no difference between strains, no difference between time points and no interaction between both factors- Draw the interaction plot- Use multiple comparisons to assess pairwise differences
Deadline: November, 29th
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The example is from a soybean balanced incomplete block experimentYield measurements (in bushels per acre) were made for 30 varietiesThere are 31 genotype levels, because one variety was duplicated (G07 and G14)The experiment consisted of 31 blocks of six plots each-Use the R function read.csv to import the data-Fit the model with fixed (and/or random) effects-Check if model assumptions are met-Build the ANOVA table and test the null hypothesis of no difference between genotypes-Use multiple comparisons to assess pairwise differencesDeadline: November, 29th