Essentials in the quantitative analysis of spatial and other data, with a particular emphasis on statistics and programming. Topics include data display, data description and summary, statistical inference and significance tests, analysis of variance, correlation, regression, and some advanced concepts, such as matrix methods, principal component analysis, and spatial statistics. Students will develop expertise in data analysis using advanced statistical software.

Prerequisites/Rules:
Credit only granted for: BIOM301, BMGT230, CCJS200, ECON230, ECON321, EDMS451, GEOG306, GEOL351, GVPT422, INST314, JOUR405, PSYC200 or SOCY201. (These courses do not necessarily meet the same major requirements-check with your advisor to see which of these courses will count for your major). General Education: FSAR
Credits: 3
Grading Method: Regular

Course Offerings

    Summer 2018 Instructor: Joanne Hall Co-Instructor: View:
    Spring 2019 Instructor: Naijun Zhou Co-Instructor: View: Syllabus
    Summer 2017 Instructor: Unlisted/TBD Co-Instructor: View: Syllabus
    Fall 2017 Instructor: Naijun Zhou Co-Instructor: View: Syllabus
    Fall 2016 Instructor: Naijun Zhou Co-Instructor: View: Syllabus
    Fall 2015 Instructor: Naijun Zhou Co-Instructor: View: Syllabus
    Winter 2015 Instructor: Unlisted/TBD Co-Instructor: View: Syllabus
    Fall 2014 Instructor: Giovanni Baiocchi Co-Instructor: View: Syllabus