I have these data:
> dput(df)
structure(list(Freq = c(41L, 31L, 11L, 0L), group = structure(c(1L,
1L, 2L, 2L), .Label = c("A", "B"), class = "factor"), Survived = structure(c(2L,
1L, 2L, 1L), .Label = c("No", "Yes"), class = "factor")), row.names = c(NA,
4L), class = "data.frame")
Freq group Survived
1 41 A Yes
2 31 A No
3 11 B Yes
4 0 B No
And I try to follow https://data-flair.training/blogs/chi-square-test-in-r/ but I'm not sure how to use the data. For example, when I use chisq.test(df$group, df$Survived) I receive
> chisq.test(df$group, df$Survived)
Pearson's Chi-squared test
data: df$group and df$Survived
X-squared = 0, df = 1, p-value = 1
which is meaningless (and didn't take into account Freq, right?)? I want to know whether there is a difference between the groups A and B.
Firstly, you need to transform the dataframe to a contingency table:
tab <- xtabs(Freq ~ ., df) # Specifically, xtabs(Freq ~ group + Survived, df)
# Survived
# group No Yes
# A 31 41
# B 0 11
Then pass it into chisq.test():
chisq.test(tab)
# Pearson's Chi-squared test with Yates' continuity correction
#
# data: tab
# X-squared = 5.8315, df = 1, p-value = 0.01574