4.2

rm(list=ls())
PATH<- "/Users/oba2311/Desktop/Minerva/Junior/SS154/4/women.csv"
dataa<-read.csv(PATH)
head(dataa)

Check whether the reservation policy was properly implemented by computing the proportions of female politicians elected for reserved seats as well as unreserved ones

reserved <- length(which(dataa$reserved==1 & dataa$female==1))
reserved

[1] 108

elected <- length(which(dataa$female==1))
elected

[1] 124

ratio <-reserved/elected
ratio

[1] 0.8709677

unreserved <- length(which(dataa$reserved==0 & dataa$female==1))
unreserved

[1] 16

elected <- length(which(dataa$female==1))
elected

[1] 124

ratio2 <-unreserved/elected
ratio2

[1] 0.1290323

Compute averages across villages. For reserved seats this proportion should be equal to 1.

all_reserved<- length(dataa$reserved==0 & dataa$village==1)
results <- data.frame(which(dataa$reserved==0 & dataa$female==1 & dataa$village==1), ncol=1)
colnames(results) <- c("not reserved, village 1", "VILLAGE")
mean(results$`not reserved, village 1`)

[1] 200.25

results/ all_reserved

results <- mean(which(dataa$reserved==1 & dataa$female==1 & dataa$village==1))
results

[1] 159.6667

mean(which(dataa$reserved==0 & dataa$female==1 & dataa$village==2))

[1] 199.25

mean(which(dataa$reserved==1 & dataa$female==1 & dataa$village==2))

[1] 158.6667