# Chi-square tests for
#of the difference between two population proportions
library(dplyr)
library(ggplot2)
library(reshape2)
library(DescTools)


#create contingency table

airtab = as.table(matrix(
  c(258,375,210, 162,155,190),
  ncol=2, nrow=3, dimnames = list(c("Sydney","Singapore","Jakarta"),
                          c("Online","Airport"))))

airtab

#set up data to generate bar charts
airtab_m <- melt(airtab, varnames = c("City",  "Method"), id.vars = "City")
#set up data frame to generate bar charts
ggplot(airtab_m %>% group_by(City) %>%   
         mutate(Percentage = round(value/sum(value),2)), 
       aes(x=City, y = Percentage, 
           fill = Method, cumulative = TRUE)) +
  geom_col() +
  geom_text(aes(label = paste0(Percentage*100,"%")), 
            position = position_stack(vjust = 0.5))




#column percentages
PercTable(airtab, 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(airtab, 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(airtab, 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
prop.test(airtab, correct=FALSE)

chisq.test(airtab, correct=FALSE)