totals                      <- c(195, 134, 38)
stems                       <- c(22,16,9)
group_stem_counts           <- matrix(c(stems, totals-stems),ncol=3,byrow=TRUE)
rownames(group_stem_counts) <- c("stem", "non-stem")
colnames(group_stem_counts) <- c("Group One","Group Two","Group Three")
group_stem_counts
#          Group One Group Two Group Three
# stem            22        16           9
# non-stem       173       118          29

chisq.test(group_stem_counts)
#
#         Pearson's Chi-squared test
#
# data:  group_stem_counts
# X-squared = 4.5225, df = 2, p-value = 0.1042
#
# Warning message:
# In chisq.test(group_stem_counts) :
#   Chi-squared approximation may be incorrect

chisq.test(group_stem_counts)$expected
#          Group One Group Two Group Three
# stem      24.97275  17.16076    4.866485
# non-stem 170.02725 116.83924   33.133515
# Warning message:
# In chisq.test(group_stem_counts) :
#   Chi-squared approximation may be incorrect

chisq.test(group_stem_counts, simulate.p.value=TRUE)
#
#         Pearson's Chi-squared test with simulated p-value (based on 2000
#         replicates)
#
# data:  group_stem_counts
# X-squared = 4.5225, df = NA, p-value = 0.1184

> p=c(.1,.2,.3,.4)
> x=c(3,5,16,10)
> chisq.test(x,p=p,simulate.p.value=TRUE,B=10000)

    Chi-squared test for given probabilities with simulated p-value (based on 10000
    replicates)

data:  x
X-squared = 4.7745, df = NA, p-value = 0.1904

> chisq.test(x,p=p,simulate.p.value=TRUE,B=10000)

    Chi-squared test for given probabilities with simulated p-value (based on 10000
    replicates)

data:  x
X-squared = 4.7745, df = NA, p-value = 0.1922