Spatial Statistics for GIS Using R
In this online training course, learn about spatial statistical analysis methods to solve geospatial problems with a focus on R. The course also explains and give examples of the analysis that can be conducted in a geographic information system.Enroll in Spatial Statistics for GIS Using R
About This Online Course
Spatial data are everywhere—and are critical to intelligence analysis in the Federal government, particularly U.S. Department of Defense and Intelligence Community agencies, and beyond.
Spatial statistical analysis "gets behind the map" to ask about the data that are plotted and pose questions about the patterns we see.
In this online training course from statistics.com, learn about the relationship between maps and the data they represent and how such data are coded in the R environment. The R programming language is built and highly optimized to perform one purpose: statistical processing,
You will explore point pattern analysis, spatial autocorrelation statistics and geostatistical interpolation to estimate values across a continuous contour type map.
After completing this online course, you will be able to describe spatial data using maps and correctly implement spatial data in R. You will also be better skilled to analyze patterns in point, area and field data and detecting non-randomness and measure spatial autocorrelation and creating contour maps.
This course utilizes Geographic Information Analysis, 2nd revised edition (Wiley, 2010), O'Sullivan, D., and Unwin, D. J., (available on Amazon). Learners must purchase the book before starting the course.
What You Will Learn
- Describe spatial data using maps
- Describe and implement the ways spatial data is represented in R
- Use spastat to analyze patterns in point data and detect non-randomness
- Use spdep to analyze patterns in area data and measure spatial autocorrelation in lattice data
- Use gstat to analyze continuous field data and create contour maps
David Unwin was a professor of geography at Birkbeck College, University of London, until he retired in 2002. He retains an emeritus chair at the college in the subject. Mr. Unwin's work using and developing spatial statistics in research stretches back some 40 years. He has authored more than 100 academic papers in the field, together with a series of texts and a edited collections at the interface between geography and computer science.
Mr. Unwin developed the world's first wholly internet-delivered Master's degree program in geographic information systems, and in 2012, was awarded the Ron F Abler Honor of the Association of American Geographers for distinguished service to the discipline. He received his Master's of Arts in Philosophy and his Bachelor of Science from the University of London, England.
Who Should Take This Course
This course is perfect for geographic information system users, scientists, business analysts, engineers and researchers in the Federal government, private-sector organizations and academia who need to create, use and analyze maps of geographic data.
You should be familiar with introductory statistics to the level of correlation and regression, as covered in these statistics.com online courses: Statistics 1 - Probability and Study Design and Statistics 2 – Inference and Association.
You should also be familiar with basic operations in R, as covered in the statistics.com online course, Introduction to R Programming.
A record of completion will be issued, along with professional development credits in the form of continuing education units upon 50-percent completion.
In addition, a Credly badge to add to your LinkedIn profile will be issued upon 80-percent completion of this online training course.
This self-paced, online training course takes place at The Institute for Statistics Education at statistics.com for four weeks. During each session week, you can participate at times of your own choosing—there are no set times for the lessons. Participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.
At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.
$649 (per person)
Register through FedLearn using the special promo code FedLearn22 and receive a five-percent discount on the original online course price.
Continuing Education Unit Credits
This online course provides 5.0 CEUs upon 50-percent completion.
This course is also recommended for 3.0 upper division college credits by the American Council on Education upon 80-percent completion.