```
## From Agresti(2007) p.39
M <- as.table(rbind(c(762, 327, 468), c(484,239,477)))
dimnames(M) <- list(gender=c("M","F"),
party=c("Democrat","Independent", "Republican"))
(Xsq <- GTest(M)) # Prints test summary
Xsq$observed # observed counts (same as M)
Xsq$expected # expected counts under the null
## Testing for population probabilities
## Case A. Tabulated data
x <- c(A = 20, B = 15, C = 25)
GTest(x)
GTest(as.table(x)) # the same
x <- c(89,37,30,28,2)
p <- c(40,20,20,15,5)
try(
GTest(x, p = p) # gives an error
)
# works
p <- c(0.40,0.20,0.20,0.19,0.01)
# Expected count in category 5
# is 1.86 < 5 ==> chi square approx.
GTest(x, p = p) # maybe doubtful, but is ok!
## Case B. Raw data
x <- trunc(5 * runif(100))
GTest(table(x)) # NOT 'GTest(x)'!
```

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