Quantitative methods for the analysis of geographical data. Topics include spatial clustering, spatial auto- correlation, spatial regression, and introductory methods for analyzing point, area (lattice), and continuous data. Lab includes the use of statistical software for exploratory spatial data analysis.
5
UnitsOptional
Grading1
PasstimeNone
Level LimitLetters and science
CollegeEven though its not a prereq don't take this class without having taken an intro stats class. As for Prof.Ganti himself, hes a bit standoffish but hes nice and very knowledgeable so ask a lot of questions! And I think this class gives you a good overview on what geographical statistical analyses there are but not so much on how/when to apply them.
While the content was very difficult, Ganti's tests didn't reflect this difficulty because they were much more based on the concepts and products of the advanced statistics you're learning, rather than "doing the math." In my opinion, I really enjoyed that he tested the course this way, and was very helpful too considering the online format.
You need 95% to get an A, the course materials are tough enough and no idea why he grades like this. He picks final questions directly from the textbook but some of them are very difficult and poorly covered in class. Reluctant replying to students' emails especially when his TA is unsure about certain theories. Not recommended.