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Spatial Analysis Techniques in R – Statistics.Com

Statistics.com
0-6 Month Online
Beginner 29-Jan-2016
Online Business Analytics
Online Self Paced 505
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The R environment provides a consistent and stable platform for spatial statistical analysis and is the computing environment of choice for most researchers in the field.

This online course, aims to:

  • Introduce the use of R for geographic information analysis. Although much of what will be covered can be accomplished using a GIS, such use is awkward and often highly inefficient;
  • Develop understanding of some topics beyond the basic courses or most standard texts.

After following the course and doing the assignments you will be able to:

  • Install and use the basic R environment;
  • Select an appropriate R package for point, lattice and geostatistical data and enter spatial data into it;
  • Create sensible maps of these same data;
  • Undertake both global and local spatial analysis of the patterns these maps reveal, using the idea of complete spatial randomness as benchmark;
  • Most important of all, critically assess the results of these analyses.

Course Program:

  • WEEK 1: Introducing R
  • WEEK 2: Point Pattern Analysis
  • WEEK 3: Area (lattice) objects
  • WEEK 4: Geostatistical data

Important Date:

January 29, 2016 to February 26, 2016

Duration:

4 Weeks

Time Requirement:

About 15 hours per week, at times of  your choosing.

Fees:

INR 37,740 (assuming $ = INR 50)

Part Time/Full Time:

Part Time

The course is aimed at anyone with experience either in spatial analysis using a standard GIS (such as ArcGIS), or who already uses R for basic non-spatial analysis wishing to extend their skills in spatial analysis using R.  Although it covers some of the same ground, students who have followed the course Spatial Statistics with GIS given by the same instructor will find that this course usefully extends their skills.

Prerequisite:

You should also be familiar with:

  • R, or, at a minimum, a command line environment,
  • Statistics – Probability and Study Design, Inference and Association
  • R
  • David Unwin
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