Random sampling is a statistical method in which each member of a population has an equal chance of being selected. The sample represents a smaller and more manageable portion of the people that can be studied and analyzed. It's a fundamental technique to gather data and make inferences about a population. Random sampling is considered a fair and unbiased sample selection method. This type of sampling is the most straightforward sample selection method.
The sample() function in R allows you to randomly sample from a specified set of (scalar) objects. You can also use the sample() function to sample rows from a data frame or a list.
Examples of how to use the sample() function:
- To randomly sample 4 numbers from 1 to 10, you would use the following code:
sample(1:10, 4)
- To randomly sample 5 letters from the alphabet, you would use the following code:
sample(letters, 5)
- To randomly permute the numbers from 1 to 10, you would use the following code:
sample(1:10)
To randomly sample 5 rows from the airquality data frame, you would use the following code:
library(datasets)
data(airquality)
set.seed(20)
idx <- seq_len(nrow(airquality))
samp <- sample(idx, 5)
airquality[samp, ]
