10.2 Week 10 Activities

  1. Read Carolan (2014), ch. 8 and ch. 9, till the end of Regression.

  2. Annotate as we normally do using proper hashtags (e.g., question, idea, stats) and doing our ABCs (i.e., “Ask a question”, “Brag about your understanding”, and “Connect another peer’s ideas”). Because this week’s topic is of great complexity, we’re going to rely on our collective wisdom to develop deeper understanding. So please seek additional resources on your own, share back via Hypothes.is or Slack, and help out a colleague.

  3. Share on Slack a brief description about your use of statistical analysis in your project (e.g., t-tests, ANOVA, regression, ERGMs).
  • Many of you appreciated seeing each other’s reports that include scripts and results. And I myself will also post a report to our community space (i.e. Slack) later this week.
  • If you are using R, please check last week’s notes on using an R Notebook for report generation.
  • If you are using Gephi, you do not have as many options as R provides. But you can export your network data populated with network measures to an external statistical software (e.g., SPSS) for additional analysis.

10.2.1 Additional resources

  • Kolaczyk and Csárdi (2014)
  • Snijders (2011)
  • Apkarian and Hanneman (2016)link


Kolaczyk, Eric D, and Gábor Csárdi. 2014. Statistical Analysis of Network Data with R: Use R! Springer New York. https://doi.org/10.1007/978-1-4939-0983-4.

Snijders, Tom A B. 2011. “Statistical Models for Social Networks.” Annual Review of Sociology 37 (1):131–53. https://doi.org/10.1146/annurev.soc.012809.102709.

Apkarian, Jacob, and Robert A Hanneman. 2016. Statistical Analysis of Social Networks. Jamaica, NY: City University of New York, York College.