This module is designed for students on social science degree programmes who do not have A-level Mathematics (e.g. in Anthropology, Law, and Social Policy).
This module is designed for students on social science degree programmes who do not have A-level Mathematics (e.g. in Anthropology, Law, and Social Policy).
16 hours and 40 minutes of lectures and 7 hours and 30 minutes of classes in the LT. A combination of classes and lectures totalling 30 hours across Lent Term. Reading week in Week 6.
Students will be expected to produce 9 other pieces of coursework and 1 other piece of coursework in the LT. Students will be presented with guided questions to answer in completing each week's reading, and discuss these in each class session. They will participate actively in presenting the answers of the questions to the group.
Saltz, J. S., & Stanton, J. M. (2017). An introduction to data science. Sage Publications. Denning, P. J., & Tedre, M. (2019). Computational thinking. MIT Press. Shan, C. (2015). The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists. Data Science Bookshelf. Schutt, R., & O'Neil, C. (2014). Doing data science: Straight talk from the frontline. O'Reilly. Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals. John Wiley & Sons. Mayer-Sch?nberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
Essay (30%, 1500 words) and presentation (10%) in the LT. Essay (60%, 2000 words) in the ST.