SamplingScientific Research Methods in GeographyMontello & SuttonCh 8 Summary

Overview

•Sampling Frames and Sampling Designs•Implications of Sampling Frames and

Designs•Spatial Sampling From Continuous Fields•Sample Size•Review/Discussion

Introduction

•Sampling is any way of selecting a subset from the entire set of entities of interest called a population

•This subset is called a sample

Sampling Frames & Designs

• How samples are obtained • What that means for the

design and interpretation of research

Population

Sampling Frame

Sample

Hierarchy of Design

Sampling Frame

Sampling Design

Non-probability Sampling

Snowball Sampling

Convenience Sampling

Probability Sampling

Simple Random Sampling

Systematic Random Sampling

Stratified Random Sampling

Cluster Sampling

Multi-stage Area Sampling

Implications of Sampling Frames & Designs

•Representativeness is the degree to which the smaller set resembles a larger set

•Generalizability refers to the question of what larger set can we validly draw conclusions about from the evidence of the smaller set?

Implications cont.

•Nonparticipation bias exists if nonparticipants are different from participants

•The sample can become less representative of the sampling frame

•Volunteer bias exists when cases get into studies by selecting themselves – “self-selection bias”▫Common in non-probability sampling

designs

Spatial Sampling From Continuous Fields•Organizing or breaking continuous space into

discrete objects, perhaps very small and numerous objects, and sampling and measuring from these objects

•Transects are linear features and a common method of this

•Quadrats are breaking continuous space into discrete polygonal features shaped like squares

•Both are probability sampling and are examples of independent spatial sampling

Spatial Sampling cont.

•Non-independent spatial sampling is focused on locations of greater change in the trend▫sampling on the basis of a model of

patterns or trends in the spatial distribution of their property of interest

•Spatial interpolation refers to making inferences back to the continuous field after sampling is completed

Sample Size• How large should a sample be?• Benefits vs. costs• Larger samples can be more representative BUT cost

more money, time and effort• Researchers don’t have unlimited resources• Consider your research goal and traditions of your

sub-discipline of geography• Power analysis & precision analysis are used to

find how large of a sample size is needed to get statistically significant results

• Effect size is the size of the relationship expresses as a proportion of noise within the data

Review/Discussion

•Give examples of some samples in geography

•Distinguish between probability and non-probability sampling

•How can you minimize non-participation and volunteer biases’ negative effects on research?

•Discuss ideas about what sample size would be good for your own thesis, or what you anticipate it being