Quiz on Randomized Complete Block Design

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RCBD analysis in R along with LSD and DNMRT test

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The blog explains step by step RCBD analysis along with LSD/DNMRT test using R and interpretation of analysis (Reading time 12 min.) Problem statement An experiment was conducted in RCBD to study the comparative performance of fodder sorghum lines under rain fed conditions. Data is furnished below. Are all lines same? If not carry out LSD test and Duncan test to compare the lines. Click here to get the data Arrange the data in Excel as shown below Replication Variety Yield 1 African tall 22.9 1 Co-11 29.5 1 FS-1 28.8 1 K-7 47 1 Co-24 28.9 2 African tall 25.9 2 Co-11 30.4 2 FS-1 24.4 2 K-7 40.9 2 Co-24 20.4 3 African tall 39.1 3 Co-11 35.3 3 FS-1 32.1 3 K-7 42.8 3 Co-24 21.1 4 African tall 33.9 4 Co-11 29.6 4 FS-1 28.6 4 K-7 3
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Completely Randomized Design Analysis in R along with LSD

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(Reading time 6 min.) Click here for Data set R-script #Fitting of linear model model <-lm(CRD$Yield ~ CRD$Treatment) #Obtains R Square and other statistics of fitted model summary <-summary(model) #Carryout ANOVA anova <-anova(model) anova #Below codes are used to obtain plots of fitted vs Residuals and Normal QQ plots par(mfrow=c(1,2)) plot(model, which=1) plot(model, which=2) #Load the package library(agricolae) #Carry out LSD test LSD <-LSD.test(CRD$Yield,CRD$Treatment,anova$`Df`[2],anova$`Mean Sq`[2]) #Generate the txt file of analysis sink("crdanalysis.txt") print("ANOVA of CRD") print(anova) print("LSD ANALYSIS") print(LSD$statistics) print(LSD$groups) sink() Output  [1] "ANOVA of CRD" Analysis of Variance Table Response: CRD$Yield                             Df            Sum Sq     Mean Sq         F value    Pr(>F)    CRD$Treatment  1               220.90   
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