Call Number | 12747 |
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Day & Time Location |
F 11:10am-1:00pm 203 Mathematics Building |
Points | 3 |
Grading Mode | Standard |
Approvals Required | None |
Instructor | Gregory M Eirich |
Type | SEMINAR |
Method of Instruction | In-Person |
Course Description | The course is designed to teach students the foundations of network analysis including how to manipulate, analyze and visualize network data themselves using statistical software. We will focus on using the statistical program R for most of the work. Topics will include measures of network size, density, and tie strength, measures of network diversity, sampling issues, making ego-nets from whole networks, distance, dyads, homophily, balance and transitivity, structural holes, brokerage, measures of centrality (degree, betweenness, closeness, eigenvector, beta/Bonacich), statistical inference using network data, community detection, affiliation/bipartite networks, clustering and small worlds; positions, roles and equivalence; visualization, simulation, and network evolution over time. |
Web Site | Vergil |
Department | Quantitative Methods/Social Sciences |
Enrollment | 70 students (105 max) as of 5:08PM Saturday, September 7, 2024 |
Subject | Quantitative Methods: Social Sciences |
Number | GR5062 |
Section | 001 |
Division | Graduate School of Arts and Sciences |
Campus | Morningside |
Note | PRIORITY QMSS STUDENTS |
Section key | 20231QMSS5062G001 |