Set working directory: Please paste the whole path to the folder where you have your files

setwd("C:/Users/MariaNelly/Documents/Dr_Mercer_Project/01_CRD")

1 Read your data set and double check that dependent and indepent variables are correctly read by R

CRD_Data <- data.frame(read.csv("CRD_Data.csv",header=T))
str(CRD_Data)
## 'data.frame':    9 obs. of  4 variables:
##  $ Plot       : int  1 2 3 4 5 6 7 8 9
##  $ Treatment  : Factor w/ 3 levels "Ambient moisture",..: 3 3 1 2 1 1 3 2 2
##  $ Replication: int  1 3 1 2 3 2 2 1 3
##  $ biomass    : num  121 118 111 131 105 ...

Perform ANOVA for CRD

Anova_CRD <- aov(biomass~Treatment,data=CRD_Data)
summary(Anova_CRD)
            Df Sum Sq Mean Sq F value   Pr(>F)    
Treatment    2 1058.0   529.0   58.04 0.000119 ***
Residuals    6   54.7     9.1                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Run a Tukey test

TukeyHSD(Anova_CRD)
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = biomass ~ Treatment, data = CRD_Data)
## 
## $Treatment
##                                        diff        lwr       upr     p adj
## Heavy Irrigation-Ambient moisture  26.50000  18.936659 34.063341 0.0000944
## Light irrigation-Ambient moisture  14.76667   7.203326 22.330008 0.0023563
## Light irrigation-Heavy Irrigation -11.73333 -19.296674 -4.169992 0.0074656

Run an LSD test

library(agricolae)
## Warning: package 'agricolae' was built under R version 3.3.3
LSD_out <- LSD.test(Anova_CRD,"Treatment",alpha=0.05,p.adj="bonferroni")
LSD_out
## $statistics
##       Mean       CV  MSerror      LSD
##   120.2556 2.510498 9.114444 8.103625
## 
## $parameters
##   Df ntr bonferroni alpha       test    name.t
##    6   3   3.287455  0.05 bonferroni Treatment
## 
## $means
##                   biomass      std r      LCL      UCL   Min   Max
## Ambient moisture 106.5000 3.675595 3 102.2350 110.7650 103.5 110.6
## Heavy Irrigation 133.0000 1.915724 3 128.7350 137.2650 130.8 134.3
## Light irrigation 121.2667 3.187998 3 117.0016 125.5317 118.4 124.7
## 
## $comparison
## NULL
## 
## $groups
##                trt    means M
## 1 Heavy Irrigation 133.0000 a
## 2 Light irrigation 121.2667 b
## 3 Ambient moisture 106.5000 c

Draw a preliminary boxplot by treatment

boxplot(biomass~Treatment, data=CRD_Data)

Use ggplot2 to make a boxplot

library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.3.3
CRD_plot <- ggplot(CRD_Data,aes(x=Treatment,y=biomass))+geom_boxplot()
CRD_plot + scale_y_continuous (name="Biomass in Kilograms") + theme_bw()