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Social Network Analysis: Statistical Models - JHU
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Social Network Analysis: Statistical Models - JHU

Master advanced network analysis techniques using R for analyzing social structures and relationships.

Course Cost

Free course

Intermediate

Skill Level

11 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Social Computing Specialization or Social Media Analytics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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What you'll learn

  • Calculate and interpret key centrality measures

  • Apply statistical models to analyze network relationships

  • Understand foundational social theories

  • Construct and analyze various network types

  • Implement ERGM and SAOM models

  • Conduct hypothesis testing with empirical data

Skills you'll gain

Network Analysis
Graph Theory
Centrality Measures
Statistical Modeling
R Programming
Social Theory
ERGM
SAOM
Data Visualization
Network Statistics

This course includes:

3.5 Hours PreRecorded video

9 assignments

Access on Mobile, Tablet, Desktop

FullTime access

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Certificate

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Share your certificate with prospective employers and your professional network on LinkedIn.

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PROVIDED BY

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Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

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There are 4 modules in this course

This comprehensive course explores advanced social network analysis, combining theoretical foundations with practical applications. Students learn to analyze complex social structures using statistical methods and R programming, focusing on centrality measures, graph theory, and social forces. The curriculum covers exponential random graph models (ERGM) and stochastic actor-oriented models (SAOM) using tools like 'statnet' and 'RSiena', preparing students for advanced network analytics.

Course Introduction

Module 1 · 14 Minutes to complete

Graph Theory and Centrality Measures

Module 2 · 4 Hours to complete

Centralization and Social Theory

Module 3 · 4 Hours to complete

Network Statistical Models

Module 4 · 3 Hours to complete

Fee Structure

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Social Network Analysis: Statistical Models - JHU

Intermediate

Skill Level

11 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.