Knowing this would be the next topic, We can directly get in. Here we see three sampling techniques. Below is the first.

Simple Random Sampling

In simplified sampling we execute below R code
Sample_Test_dataset = Test_dataset[sample(nrow(Test_dataset), 1000, replace = F ),]

Sample_Test_dataset - Sample
Test_dataset - Dataset from which we take sample
sample - It is a built in function
nrow() - First arguement for sample function is the total number of rows of the dataset
1000 - Number of rows taken for sample
replace = F - Rows once taken should not be taken again

Since this is a row level operation, we end up with comma.. in the code.
The original dataset is having 13k rows. See below

As per above programming the sample should have 1k observations.. see below..

Hope the above one is clear. The next sampling is below

Stratified Sampling

stratas = strata(Test_dataset, c(“SellerG”), size = c(60, 100, 100, 100, 50, 60, 1, 1, 1), method = “srswor”) stratas