ldecola.net/edu/umbc/spatialR/syllabus_679.html
Meets weekly, 2018 Sep 3 to Oct 8, 18:1520:30 Eastern Time (UTC5)
Location: *Kendall 4212 (first and last sessions) and online via
Blackboard Collaborate
DATE  TOPIC  LAB  **TEXT  ASSIGNMENT 

*Sep 10  1. Intro to R  New Haven  1, 2, 4 

Sep 17  2. Points  burglaries  3.4.4, 6  1. Maps and stats 
Sep 24  3. Polygon  tracts  2.4, 3.14  
Oct 1  4. Raster  Meuse  5.89  2. Point pattern 
Oct 8  5. Graphs  TBA  7  
*Oct 15  6. Inclass presentations  3. Submit by Oct 14 24:59 
Lee De Cola
LDECOLA@COMCAST.NET
DATA to Insight, Reston VA
Phone: 015713150577
hours: 10:0018:00
the R programming environment
about the mathematics of space
the fundamentals of spatial data structures
to do quantitative analysis of spatial processes
to conduct and present original research
Realtime lab exercises using R interactively and collaboratively
Readings and significant coding exercises
Three assignments, including a final project presented in the last session
R language and particularly its
spatial analysis tools.
NOTE: Priddy Librarian Amy Trost is offerring Intro to R workshops on 2018 Sep 4 at 1600 and Sep 24 at 1230.
Spreadsheet (e.g. Excel) often useful for restructuring data into Rreadable formats.
**REQUIRED: Brunsdon, C. and L. Comber (2015) An introduction to R for spatial analysis & mapping Los Angeles, SAGE. The syllabus table above shows the relevant (sub)sections, but as the book covers a lot more material than we can, i'll suggest the pages that you should code yourself.
RECOMMENDED: Adler, J. (2010). R in a nutshell Sebastopol, CA, O'Reilly. There are many intro R books around; this is one I like.
Bivand, Roger, et al. (2013) Applied spatial data analysis with R New York, Springer. An excellent but quite technical review of our topics.
Waller, L. A. and C. A. Gotway (2004) Applied spatial statistics for public health data Hoboken, N.J, John Wiley & Sons.
Cressie, N. A. C. (1991) Statistics for spatial data New York, Wiley.