# Practicals 5
test.res<-chisq.test(c(10, 25, 18, 6), p=rep(1/4, 4))
# Chi-squared test for given probabilities
# 
# data:  c(10, 25, 18, 6)
# X-squared = 14.559, df = 3, p-value = 0.002235

unclass(test.res)

test.res$observed-test.res$expected
# [1] -4.75 10.25  3.25 -8.75

(test.res$observed-test.res$expected)/test.res$expected
# [1] -0.3220339  0.6949153  0.2203390 -0.5932203

chisq.test(c(125, 60, 50, 12),
           p=c(9/16, 3/16, 3/16, 1/16))
# Chi-squared test for given probabilities
# 
# data:  c(125, 60, 50, 12)
# X-squared = 6.5025, df = 3, p-value =
#   0.08956

pchisq(5.04, df=3, lower.tail=F)
1-pchisq(5.04, df=3)

qchisq(0.05, df=3, lower.tail = F)
qchisq(0.01, df=3, lower.tail = F)

qchisq(0.05, df=8, lower.tail = F)
qchisq(0.01, df=8, lower.tail = F)

chisq.test(c(6,4))
# Chi-squared test for given probabilities
# 
# data:  c(6, 4)
# X-squared = 0.4, df = 1, p-value = 0.5271

chisq.test(c(60,40))
# Chi-squared test for given probabilities
# 
# data:  c(60, 40)
# X-squared = 4, df = 1, p-value = 0.0455

chisq.test(c(600,400))
# Chi-squared test for given probabilities
# 
# data:  c(600, 400)
# X-squared = 40, df = 1, p-value = 2.54e-10


chisq.test(c(12,6,5,0), 
       p=c(9/16,3/16,3/16,1/16))