Weekly schedule

Week	Topic	Reading	Extra reading	In-class tasks
01	Introduction and overview	DASS Ch1.3-7	HOPR Ch1, Ch2, Ch3	Individual quiz; Group problem set
02	Measuring and summarising data	DASS Ch1.8	HOPR Ch5, Ch6	Individual quiz; Group problem set
03	Data visualisation	R4DS Ch3	FA Ch1, Ch2, TA Ch2	Individual quiz; Group problem set
04	Data collection and manipulation	R4DS Ch5	HOPR Ch7, Ch8; R4DS Ch18	Individual quiz; Group problem set
05	Bivariate association and causality	DASS Ch2		Individual quiz; Group problem set
06	Dimension reduction	I2SL Ch12.2; Wattenberg, Viégas & Johnson	RMD Ch1, Ch2, Ch3	Individual quiz; Group problem set
07	Conducting reproducible research	DASS Ch3; Kitchin	boyd & Crawford; Floridi	Individual quiz; Group problem set
08	Normal curve & confidence intervals	DASS Ch6		Individual quiz; Group problem set
09	Hypothesis testing	DASS Ch7		Individual quiz; Group problem set
10	Simple regression	DASS Ch4		Individual quiz; Group problem set
11	Multiple regression	DASS Ch5		Individual quiz; Group problem set
12	Logistic regression and advanced topics	I2SL Ch4.1-3; QSS Ch5.2-3.1		Individual quiz; Group problem set
13	Computational text analysis	TMWR Ch1, Ch2, Ch3, Ch4, Ch6	QSS Ch5.1	Group problem set

Text book:

• Llaudet, E., & Imai, K. (2022). Data analysis for social science: A friendly and practical introduction. Princeton University Press. https://press.princeton.edu/books/hardcover/9780691199429/data-analysis-for-social-science (DASS)
  • Publicly and fully available online: NO
  • Online access through library: NO
  • Copy available through library: YES

Other texts:

• boyd, danah, & Crawford, K. (2012). Critical questions for big data. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878
  • Publicly and fully available online: NO
  • Online access through library: YES link
• Cairo, A. (2012). The Functional Art: An introduction to information graphics and visualization. New Riders. https://learning.oreilly.com/library/view/the-functional-art/9780133041187/ (FA)
  • Publicly and fully available online: NO
  • Library access: YES link
    • Online access: YES link
    • Hard Copy: YES
• Cairo, A. (2016). The Truthful Art: Data, Charts, and Maps for Communication. Pearson Education. https://learning.oreilly.com/library/view/the-truthful-art/9780133440492 (TA)
  • Publicly and fully available online: NO
  • Library access: YES link
    • Online access: YES link
    • Hard Copy: NO
• Floridi, L. (2012). Big data and their epistemological challenge. Philosophy & Technology, 25(4), 435–437. https://doi.org/10.1007/s13347-012-0093-4
  • Publicly and fully available online: YES link
• Grolemund, G. (2014). Hands-on programming with R. O’Reilly. https://rstudio-education.github.io/hopr/ (HOPR)
  • Publicly and fully available online: YES link
• James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning: With applications in R. Springer. https://www.statlearning.com/ (I2SL)
  • Publicly and fully available online: YES link
• Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1(1). https://doi.org/10.1177/2053951714528481
  • Publicly and fully available online: YES link
• Imai, K. (2017). Quantitative social science: An introduction. Princeton University Press. https://press.princeton.edu/books/paperback/9780691175461/quantitative-social-science (QSS)
  • Publicly and fully available online: NO
  • Library access: NO
• Silge, J., & Robinson, D. (2017). Text mining with R: A tidy approach. O’Reilly. https://www.tidytextmining.com/ (TMWR)
  • Publicly and fully available online: YES link
• Xie, Y., Allaire, J. J., & Grolemund, G. (2019). R Markdown: The definitive guide. CRC Press. https://bookdown.org/yihui/rmarkdown/ (RMD)
  • Publicly and fully available online: YES link
• Wickham, H., & Grolemund, G. (2017). R for data science. O’Reilly. https://r4ds.had.co.nz/ (R4DS)
  • Publicly and fully available online: YES link
• Wattenberg, M., Viégas, F., & Johnson, I. (2016). How to use t-SNE effectively. Distill, 1(10), e2. https://doi.org/10.23915/distill.00002
  • Publicly and fully available online: YES link