Sample

The world is infinitely complex, and for that reason it become important when collecting geographic data to make the data collected abstract. Sampling is a set of techniques used to make data less complex while maintain some of its properties, specifically the properties we would like to study. There are various types of sampling including: simple random sampling, systematic sampling, application-specific sampling, and stratified sampling.

Simple random Sampling : Each element in a sample frame is assigned a unique number and a specific number are drawn at random from the sample frame.

Systematic Sampling: A regular sampling interval is determined and a specific number is drawn from the sample frame at this interval.

Application-Specific Sampling:

Stratified Sampling: Is the process of dividing the item to be sampled (population or area) into homogeneous subgroups before sampling. Then random samples are drawn from each substratum, this allows for an increased accuracy in the representativeness of the sample.

Sources

Authors	Robert McCleary, Olaf Johnson
Editors	Jarom Randall
BoK Topics	GD9
311 Weeks	2
Tags	Data Collection