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#mc
# # create subsets for each soil Series
PeoC = subset(mc, S_Series== "PeoC")
KkoC = subset(mc, S_Series== "KkoC")
PenB = subset(mc, S_Series== "PenB") 
summary.list(data1)  # KkoC
## $Total_No.Samples.with.NA.removed
## [1] 60
## 
## $Count.of.NA
## [1] 0
## 
## $Mean
## [1] 1.673217
## 
## $Median
## [1] 1.6835
## 
## $Max...Min
## [1] 0.975 2.360
## 
## $Range
## [1] 2.484
## 
## $Variance
## [1] 0.1074834
## 
## $Std.Dev
## [1] 0.3278467
## 
## $Coeff.Variation.Prcnt
## [1] 19.5938
## 
## $Std.Error
## [1] 0.04232482
## 
## $Quantile
##      0%     25%     50%     75%    100% 
## 0.97500 1.44650 1.68350 1.93925 2.36000
summary.list(data)  # PenB
## $Total_No.Samples.with.NA.removed
## [1] 65
## 
## $Count.of.NA
## [1] 0
## 
## $Mean
## [1] 1.591369
## 
## $Median
## [1] 1.556
## 
## $Max...Min
## [1] 0.767 3.251
## 
## $Range
## [1] 2.484
## 
## $Variance
## [1] 0.1627195
## 
## $Std.Dev
## [1] 0.4033851
## 
## $Coeff.Variation.Prcnt
## [1] 25.3483
## 
## $Std.Error
## [1] 0.05003376
## 
## $Quantile
##    0%   25%   50%   75%  100% 
## 0.767 1.329 1.556 1.775 3.251
summary.list(data2) # PeoC
## $Total_No.Samples.with.NA.removed
## [1] 25
## 
## $Count.of.NA
## [1] 0
## 
## $Mean
## [1] 1.3474
## 
## $Median
## [1] 1.364
## 
## $Max...Min
## [1] 0.853 1.849
## 
## $Range
## [1] 2.484
## 
## $Variance
## [1] 0.07060033
## 
## $Std.Dev
## [1] 0.2657072
## 
## $Coeff.Variation.Prcnt
## [1] 19.72
## 
## $Std.Error
## [1] 0.05314145
## 
## $Quantile
##    0%   25%   50%   75%  100% 
## 0.853 1.140 1.364 1.498 1.849
library(agricolae)
# THE ANOVA FOR ORGANIC MATTER CONTENT
model<-aov(OM ~ S_Series, data=mc)
summary(model)
##              Df Sum Sq Mean Sq F value   Pr(>F)    
## S_Series      2   5.59  2.7951   7.492 0.000798 ***
## Residuals   147  54.85  0.3731                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# THE ANOVA FOR TOTAL CARBON
model<-aov(Total_C ~ S_Series, data=mc)
summary(model)
##              Df Sum Sq Mean Sq F value   Pr(>F)    
## S_Series      2  1.881  0.9403   7.492 0.000798 ***
## Residuals   147 18.450  0.1255                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# POSTHOC TEST
out <- HSD.test(model,"S_Series", group=TRUE,console=TRUE, # Soil S_Series
                main="IMPACT OF SOIL SERIES ON TOTAL_C")
## 
## Study: IMPACT OF SOIL SERIES ON TOTAL_C
## 
## HSD Test for Total_C 
## 
## Mean Square Error:  0.1255101 
## 
## S_Series,  means
## 
##       Total_C       std  r   Min   Max
## KkoC 1.673217 0.3278467 60 0.975 2.360
## PenB 1.591369 0.4033851 65 0.767 3.251
## PeoC 1.347400 0.2657072 25 0.853 1.849
## 
## Alpha: 0.05 ; DF Error: 147 
## Critical Value of Studentized Range: 3.348424 
## 
## Groups according to probability of means differences and alpha level( 0.05 )
## 
## Treatments with the same letter are not significantly different.
## 
##       Total_C groups
## KkoC 1.673217      a
## PenB 1.591369      a
## PeoC 1.347400      b
plot(out)

# THE ANOVA FOR TOTAL NITROGEN
model<-aov(Total_N ~ S_Series, data=mc)
summary(model)
##              Df  Sum Sq  Mean Sq F value   Pr(>F)    
## S_Series      2 0.01396 0.006980   7.481 0.000805 ***
## Residuals   147 0.13715 0.000933                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

PLOTS OF TOTAL C, TOTAL N and OM

tinytex::install_tinytex()