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Interactive Teaching Tools for Spatial Sampling

Author

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  • Bowman, Adrian
  • Gibson, Iain
  • Scott, E. Marian
  • Crawford, Ewan

Abstract

The statistical analysis of data which is measured over a spatial region is well established as a scientific tool which makes considerable contributions to a wide variety of application areas. Further development of these tools also remains a central part of the research scene in statistics. However, understanding of the concepts involved often benefits from an intuitive and experimental approach, as well as a formal description of models and methods. This paper describes software which is intended to assist in this understanding. The role of simulation is advocated, in order to explain the meaning of spatial correlation and to interpret the parameters involved in standard models. Realistic scenarios where decisions on the locations of sampling points in a spatial setting are required are also described. Students are provided with a variety of sampling strategies and invited to select the most appropriate one in two different settings. One involves water sampling in the lagoon of the Mururoa Atoll while the other involves sea bed sampling in a Scottish firth. Once a student has decided on a sampling strategy, simulated data are provided for further analysis. This extends the range of teaching activity from the analysis of data collected by others to involvement in data collection and the need to grapple with issues of design. It is argued that this approach has significant benefits in learning.

Suggested Citation

  • Bowman, Adrian & Gibson, Iain & Scott, E. Marian & Crawford, Ewan, 2010. "Interactive Teaching Tools for Spatial Sampling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i13).
  • Handle: RePEc:jss:jstsof:v:036:i13
    DOI: http://hdl.handle.net/10.18637/jss.v036.i13
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    Cited by:

    1. Martin Meermeyer, 2014. "LinRegInteractive: An R Package for the Interactive Interpretation of Linear Regression Models," Schumpeter Discussion Papers SDP14014, Universitätsbibliothek Wuppertal, University Library.
    2. Pebesma, Edzer & Bivand, Roger & Ribeiro, Paulo Justiniano, 2015. "Software for Spatial Statistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i01).

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