## -----------------------------------------------------------------------------
library(agro)
ff <- get_data_from_uri("https://doi.org/10.34725/DVN/90SBOT", ".")
ff


## -----------------------------------------------------------------------------

data <- read.delim(ff[1])


## -----------------------------------------------------------------------------
# Split data according to fertilisation scheme
mydata <- split(data, data$Fertilisationscheme)

# For mineral fertilization
mineralf <- mydata$`Mineral fertilization`

# For no fertilization
nof <- mydata$`No fertilization`

# For Non sterilized compost
nscompost <- mydata$`Non sterilized compost`
  
# For sterilized compost
scompost <- mydata$`Sterilized compost`
  
# For C.calothyrsus. 
con <- mydata$Calliandra


## -----------------------------------------------------------------------------

# Mineral fertilizetion vs. Control
t.test(mineralf$Plantvigor, con$Plantvigor, paired = TRUE)

# No fertilizetion vs. Control
t.test(nof$Plantvigor, con$Plantvigor, paired = TRUE)

# Non sterilized compost vs. Control
t.test(nscompost$Plantvigor, con$Plantvigor, paired = TRUE)

# Sterilized compost vs. Control
t.test(scompost$Plantvigor, con$Plantvigor, paired = TRUE)


## -----------------------------------------------------------------------------
# Subset new data frame
newdata <- data[ , -c(1:7,14)]

# Make a correlation matrix table 
round(cor(newdata), 2)