Introduction to Statistical Analysis of Network Data Winter 2024

Class Details

Networks are everywhere in our connected world, from social networks like facebook and twitter, to information networks like citation and coauthors, from biological network like neural and ecological networks, to technological networks like internet connections or power grids. In recent years, there has been an explosion of network data. How do we learn and represent information from these data? In this course, you will see examples from different types of networks. We will learn how to organize, visualize and describe network data using proper tools in R. Additionally since things are connected in networks, we will explore statistical methods to overcome this challenge with dependent data. Tentatively coursework includes 2-3 class meetings per week for lectures and hands-on computer labs. Students will finish a final project analyzing a network dataset of their interest and share their findings in written or oral form.
The Class: Format: lecture
Limit: 10
Expected: NA
Class#: 1316
Grading: pass/fail only
Requirements/Evaluation: class participation, lab assignment, final project (short paper or oral presentation)
Prerequisites: one introductory statistic course (STAT 201 or STAT 202) or permission of the instructor
Enrollment Preferences: Students with a statistics background and prior experience working with R

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