## Read the data:
## 
or = read.table('../../Data/symphony.txt', header=FALSE, skip=4,
                col.names=c('name', 'total', 'violin_m', 'violin f', 'viola m', 'viola_f', 'cello_m', 'cell_f', 'bass_m', 'bass_f'))
##print(or)

no = dim(or)[1]

F = c(or[, 4], or[, 6], or[, 8], or[, 10]) ## Female counts
##print(F)

M = c(or[, 3], or[, 5], or[, 7], or[, 9]) ## Male counts
##print(M)

inst = rep(c('violin', 'viola', 'cello', 'bass'), each=no)
name = rep(or[, 1], 4)
size = or[, 2]
orch = data.frame(cbind(F, M, size, inst, name))
orch$size = as.numeric(as.character (orch$size))
##print(orch)

resp = cbind(orch$F, orch$M) ##


## Study if the proportion of women changes depending on the instrument type:
##
inst = orch$inst
print(inst)

logit_model = glm(resp ~ inst, family=binomial())
print(summary(logit_model))


## Study if the size is a useful covariate:
##
logit_model = glm(resp ~ orch$size, family=binomial())
print(summary(logit_model))


## Study if name is a useful covariate:
##
logit_model = glm(resp ~ orch$name, family=binomial())
print(summary(logit_model))