#############################################################
## R code to accompany the textbook
## Statistics: The Art & Science of Learning from Data
## by A. Agresti, C. Franklin and B. Klingenberg
## 5th Edition, Pearson 2021
## Web: ArtofStat.com
## Copyright: Bernhard Klingenberg
############################################################

###################
###  Chapter 8  ###
###  Example 11 ###
###################

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## Percentile Confidence Interval ##
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# Reading in the data
delays <- read.csv(file='https://raw.githubusercontent.com/artofstat/data/master/Chapter7/atl_departure_delay.csv')

# To make 10,000 bootstrap samples and compute each sample mean
bootmean <- c()
for (i in 1:10000) {
  bootmean[i] <- mean(sample(delays$minutes, replace = TRUE))
}

# To obtain the 2.5th and 97.5th percentiles of the bootstrapped means
quantile(bootmean, c(0.025, 0.975))