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
CollegeFor Class 111B, attendance isn't really mandatory for lecture and lab. You will be coding using R-Studio. The labs take a couple hours to complete and there isn't a final or midterm just canvas quizies. When i took the class the TAs heavy accent made it impossible to learn anything. I defiantly recommend the class.
Pretty smart professor and an easy A. Very interesting if you are interested in transportation if not still a cool class.
A caring professor for students. This course is graded by 8 labs and weekly quizzes. Quizzes are based on his lectures, which are easy if you participate or watch the slides. Labs are R coding exercises, follow the instructions it will be easy. Goulias is a n expert, definitely recommend this course to folks who are fond of transportation systems
There are seven labs, a midterm, a group project, and a final solo project. Labs can be tricky so attendance definitely helps but it's not mandatory because everything is online on R. Prof Goulias is very kind and tries his best to make lectures interesting.
Prof Goulias provides a pretty extensive introduction to transportation planning, R, and data management. The course doesn't ask much of you but Goulias still maintains passion for what he is teaching and actively wants you to succeed. One of the friendliest and kindest professors I've ever met so far at UCSB.
Almost dropped this class and Im so happy I didnt! Goulias is so nice and funny, one of the best professors I've had at UCSB. The class was only 2 papers and a take home final, super easy and really interesting topics considering our time period.