#Chi-Square test of Independence

library(dplyr)
library(ggplot2)
library(reshape2)
library(DescTools)


#create contingency table

fftab = as.table(matrix(c(62, 58, 48, 22, 15, 29, 5, 7, 10, 73, 75, 103),
  ncol=4, nrow=3, dimnames = list(c("Sydney","Singapore","Jakarta"),
                                  c("Bronze","Silver", "Gold","None"))))
fftab


#set up data to generate bar charts
fftab_m <- melt(fftab, varnames = c("City",  "Status"), id.vars = "City")
#set up data frame to generate bar charts
ggplot(fftab_m %>% group_by(City) %>%   
         mutate(Percentage = round(value/sum(value),3)), 
       aes(x=City, y = Percentage, 
           fill = Status, cumulative = TRUE)) +
  geom_col() +
  geom_text(aes(label = paste0(Percentage*100,"%")), 
            position = position_stack(vjust = 0.5))


#column percentages
PercTable(fftab, row.vars = NULL, col.vars = NULL, justify = "right",
          freq = TRUE, rfrq = "001", expected = FALSE, residuals = FALSE,
          stdres = FALSE, margins = c(1,2), digits = 0)

#row percentages
PercTable(fftab, row.vars = NULL, col.vars = NULL, justify = "right",
          freq = TRUE, rfrq = "010", expected = FALSE, residuals = FALSE,
          stdres = FALSE, margins = c(1,2), digits = 0)

#expected frequencies, residuals
PercTable(fftab, row.vars = NULL, col.vars = NULL, justify = "right",
          freq = TRUE, rfrq = "000", expected = TRUE, residuals = TRUE,
          stdres = FALSE, margins = c(1,2), digits = NULL)


#chi-square test

chisq.test(fftab, correct=FALSE)