Question

I have the following code in R:

set.seed(1)

sample_sd <- matrix(NA, nrow = 1000, ncol = 10,
dimnames = list(NULL, c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)))

for (N in seq(10, 100, by = 10)) {

samples <- replicate(1000, rnorm(N, mean = 100, sd = 30))

sd_samples <- apply(samples, 2, sd)

sample_sd[, as.character(N)] <- sd_samples

Answer 1

The provided R code generates a matrix (sample_sd) and calculates standard deviations for samples from normal distributions with different sizes.

Step-by-step explanation:

The code provided in R is generating a matrix called sample_sd, with 1000 rows and 10 columns. The column names of the matrix are numeric values 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100. The code then performs a loop starting from N=10, incrementing by 10 up to N=100.

Within each iteration, it generates 1000 samples of N random numbers from a normal distribution with a mean of 100 and a standard deviation of 30. The standard deviations of each sample are calculated using the apply function and stored in the corresponding column of the sample_sd matrix.