GGR 270 – Lecture 6 – October 20, 2010

Sampling

Aim of inferential stats is to generalize about characteristics of larger population

So, need a process to obtain a sample

Sampling can be spatial or non-spatial

Therefore, an essential skill for any geographer to have

Why Sample?

Necessary is cases o extremely large populations

Efficient and cost-effective way of understanding the population

Highly detailed information can be obtained easily

Allows for follow-up activity or repetition

Sampling Error

If a sample is representative of the population then it will accurately reflect the

characteristics of the population, without bias

Element of randomness must be introduces to preserve the representative sample

Can never eliminate bias, only minimize it

Reducing bias means reducing error

Precision and accuracy help categorize sources of error

Sampling Designs

Different number of sampling designs:

www.notesolution.com

## Document Summary

Ggr 270 lecture 6 october 20, 2010. aim of inferential stats is to generalize about characteristics of larger population. so, need a process to obtain a sample. Therefore, an essential skill for any geographer to have. necessary is cases o extremely large populations. efficient and cost-effective way of understanding the population. highly detailed information can be obtained easily. If a sample is representative of the population then it will accurately reflect the characteristics of the population, without bias. element of randomness must be introduces to preserve the representative sample. can never eliminate bias, only minimize it. precision and accuracy help categorize sources of error. different number of sampling designs: www. notesolution. com: simple random, systematic sampling, stratified. can also have a series of spatial sampling designs: use cartesian coordinates, simple, stratified random, transect. sample statistics will change or vary for each random sample selected.