Visualization For Analytics

Host University

George Mason University

Semester

Summer 2024

Course Number

STAT 515 001

Credits

3

Discipline

Data Science/Analytics

Instructor

Adetokunbo Fadahunsi (tfadahun@gmu.edu)

Times and Days

Asynchronous

Course Information

Introduces multivariate regression and random forests for modeling data. Addresses data access, variable selection and model diagnostics. Introduces foundations for visual thinking. Reviews common statistical graphics such as dot plots, box plots, q-q plots. Addresses more advanced methods such as scatterplot matrices enhanced by smoothed or density contours, and search tools for finding graphics with suggestive patterns. Notes: Course will introduce R software for analysis. A final project will involve visualization of a real data set.Offered by Statistics. May not be repeated for credit.

Prerequisites

STAT 250 or equivalent.