In GegznaV/BioStat: Routines for Basic (Bio)Statistics

knitr::opts_chunk$set(fig.width = 5, 
                      fig.height = 3)
library(car)
library(BioStat)

Input =("
Location Turbidity
 a        1.0
 a        1.2
 a        1.1
 a        1.1
 a        2.4
 a        2.2
 a        2.6
 a        4.1
 a        5.0
 a       10.0
 b        4.0
 b        4.1
 b        4.2
 b        4.1
 b        5.1
 b        4.5
 b        5.0
 b       15.2
 b       10.0
 b       20.0
 c        1.1
 c        1.1
 c        1.2
 c        1.6
 c        2.2
 c        3.0
 c        4.0
 c       10.5
")


Data = read.table(textConnection(Input), header = TRUE)

gg_boxplot_plus(Turbidity ~ Location, data = Data)

ggplot(Data, aes(Turbidity)) +
    geom_histogram(bins = 10, color = "black", aes(y = ..density..)) +
    stat_normal_density(color = "red", lwd = 1)

model = lm(Turbidity ~ Location,
           data = Data)

Anova(model, type = "II")

x = (residuals(model))

library(rcompanion)

plotNormalHistogram(x)

qq_plot(residuals(model))

plot(model)

library(rcompanion)

Data$Turbidity_tuk =
    transformTukey(Data$Turbidity,
                   plotit = FALSE)

Turbidity = c(1.0, 1.2, 1.1, 1.1, 2.4, 2.2, 2.6, 4.1, 5.0, 10.0, 4.0, 4.1, 4.2, 4.1, 5.1, 4.5, 5.0, 15.2, 10.0, 20.0, 1.1, 1.1, 1.2, 1.6, 2.2, 3.0, 4.0, 10.5)


library(rcompanion)

plotNormalHistogram(Turbidity)

library(MASS)

Box = boxcox(Turbidity ~ 1,              # Transform Turbidity as a single vector
             lambda = seq(-6,6,0.1)      # Try values -6 to 6 by 0.1
             )

data.frame(Box)