Key concepts

• Good data management practices (Gentzkow & Shapiro, 2014; Wilson et al., 2017)
• Tidy vs. messy data (Wickham, 2014)
• Levels of measurement (Meier et al., 2014)

Before class

Required readings

1. Gentzkow, M., & Shapiro, J. M. (2014). Code and Data for the Social Sciences: A Practitioner’s Guide.
2. Wilson, G., Bryan, J., Cranston, K., Kitzes, J., Nederbragt, L., & Teal, T. K. (2017). Good Enough Practices in Scientific Computing. PLOS Computational Biology, 13(6), e1005510. https://doi.org/10.1371/journal.pcbi.1005510
3. Wickham, H. (2014). Tidy Data. The Journal of Statistical Software, 59(10).
4. Meier, K. J., Brudney, J. L., & Bohte, J. (2014). Measurement. In Applied Statistics for Public and Nonprofit Administration.

In class

• Lecture on key concepts (1.5h).
• Hands-on practice (1h):
  • Paper practice (15 mins)
  • In-class practice (45 mins)
• Review progress of assignments (15 mins): Learning plan.

After class

• Learning plan proposal (draft, not for grading) due this week.
• Learning plan proposal final due next week.
• Complete Paper Practice of W4
• Review In-class Practice of W4