#############################################################
## R code to reproduce statistical analysis in the textbook:
## Agresti, Franklin, Klingenberg
## Statistics: The Art & Science of Learning from Data
## 5th Edition, Pearson 2021
## Web: ArtofStat.com
## Copyright: Bernhard Klingenberg
############################################################

###################
###  Chapter 2  ###
###  Example 17 ###
###################

################
##  z-Scores  ##
################

# Read in CO2 pollution values:
euCO2 <- read.csv(file='https://raw.githubusercontent.com/artofstat/data/master/Chapter2/EU_CO2.csv')
attach(euCO2) # so we can refer to variable names

# To find the z-score for the CO2 value of Luxembourg
zScoreLuxembourg <- (21.4 - mean(CO2)) / sd(CO2)
zScoreLuxembourg

# To find the z-score for the CO2 value of the United States
zScoreUS <- (16.9 - mean(CO2)) / sd(CO2)
zScoreUS

# Basic Box Plot
boxplot(CO2, horizontal = TRUE, xlab = expression('CO'[2]*' Emission per Capita (metric tons)'))

# A better-looking box plot can be obtained with the ggplot2 library
# To install it, type install.packages('ggplot2')
library(ggplot2)
ggplot(data.frame(CO2), aes(x = '', y = CO2)) + 
  geom_boxplot(width = 0.3, fill = 'tan') +
  coord_flip() +
  labs(x = '', y = expression('CO'[2]*' Emission per Capita (metric tons)'), 
       title = 'EU Air Pollution Data') +
  theme_classic() + 
  scale_y_continuous(limits = c(0,24), 
                     breaks = seq(0,22,2), 
                     expand = c(0,0)) + 
  theme(axis.line.y=element_blank(),
        axis.text.y=element_blank(),
        axis.ticks.y=element_blank(),
        axis.title.y=element_blank()
        )