Answer:
Step-by-step explanation:
The described sampling method is called "Stratified Random Sampling."
In stratified random sampling, a population is divided into distinct subgroups or strata based on certain characteristics that are relevant to the study. Each subgroup or stratum is then treated as a separate sampling unit. Within each stratum, random sampling is used to select individuals or elements to be included in the sample. This ensures that each subgroup is represented in the sample, and the sample is more representative of the entire population.
In your case, the forest is divided into different plots of land (the strata), and within each plot, you randomly select different trees to measure their width. This approach helps ensure that you obtain a more accurate and representative estimate of the average width of trees in the entire forest.