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Sampling

Sampling. Scientific Research Methods in Geography Montello & Sutton Ch 8 Summary. Overview. Sampling Frames and Sampling Designs Implications of Sampling Frames and Designs Spatial Sampling From Continuous Fields Sample Size Review/Discussion. Introduction.

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Sampling

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  1. Sampling Scientific Research Methods in Geography Montello & Sutton Ch 8 Summary

  2. Overview • Sampling Frames and Sampling Designs • Implications of Sampling Frames and Designs • Spatial Sampling From Continuous Fields • Sample Size • Review/Discussion

  3. 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

  4. Sampling Frames & Designs • How samples are obtained • What that means for the design and interpretation of research

  5. Hierarchy of Design

  6. 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?

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

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