Times Series

Bhawna G. Panwar

1 minute read

Load data

population <- read.csv("C:/Users/Bhawna/Documents/blog/data/world-population.csv", sep=",", header=TRUE)

Default plot

plot(population$Year, population$Population, type="l")

Adjust axis

plot(population$Year, population$Population, type="l", ylim=c(0, 7000000000), xlab="Year", ylab="Population") Reference: world_population.csv was obtained from Flowdata.com

How does the Bootstrap method work?

Bhawna G. Panwar

1 minute read

Question of the day? Suppose we have a normal population with a mean of 3 and a standard deviation of 1, how would we illustrate the bootstrap method here? set.seed(1) srs <- rnorm(25, mean=3) resamps <- replicate(1000, sample(srs, 25, TRUE), simplify = FALSE) x_bar_star <- sapply(resamps, mean, simplify =TRUE) Let’s create a histogram here and fit normal curve. hist(x_bar_star, breaks = 40, prob = TRUE) curve(dnorm(x, 3, 0.2), add = TRUE) We can calculate the difference now.