Task 3

# Task 3
install.packages('MASS')
library('MASS')
data('birthwt')

# 1 for underweigth, 0 for the opposite
wtCategory <- c()

for (i in 1:length(birthwt$bwt)) {
  if (birthwt$bwt[i] < 2500) {
    wtCategory <- c(wtCategory, 1)
  } else {
    wtCategory <- c(wtCategory, 0)
  }
}

boxplot(birthwt$age ~ wtCategory)

underWt <- birthwt$age[which(birthwt$bwt < 2500)]
notUnderWt <- birthwt$age[which(birthwt$bwt >= 2500)]

shapiro.test(underWt) # > alpha = 0.05
shapiro.test(notUnderWt) # < alpha = 0.05

# the distribution of ones with not underweight is not normal so we can't use Students t test
# we will use the Wilcoxon test
wilcox.test(x = underWt, y = notUnderWt, conf.int = T, conf.level = 0.2, alternative = "greater")

# we cannot throw away the hypothesis that younger women give birth to younger babies