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I work with second-year students who have backgrounds in Sociology, Politics, and Criminology. Data Analysis II provides an overview of the strengths and weaknesses of the OLS regression model from a classical statistics perspective. I lead the lab sessions where students learn how to construct data sets from individual and aggregate level data, how to analyze these data using appropriate statistical tools, ranging from simple t-test for mean comparison to more advanced multivariate regression analysis, and how to best communicate summary statistics and estimation results by using appropriate techniques for visual presentation.
In Data Analysis III, students are introduced to advanced quantitative techniques for social data analysis. The primary emphasis of the course is data manipulation and visualization in R, with particular emphasis on the package Tidyverse. The teaching data used in this module is from Understanding Society, the UK Household Longitudinal Study. I am responsible for providing onsite technical assistance (two hours a week) and additional office hours (two hours a week), assisting students with their assignments, and assessing the data analysis assignments as the first marker. This role allows me to provide one-to-one tutorials to students who have been unable to attend lectures and have had difficulty keeping up with their progress. Coding proved to be a challenge for some students. Our collaborative efforts, however, led us to realize that the challenge did not lie within the code itself, but rather in understanding the underlying logic of the real data and using the actual data to tell an engaging story.
