Many if not most social research questions are concerned with questions of causality, e.g. what are the causes of good and bad things in society? Only if we understand the causes can we hope to modify the good/bad effects.
Much if not most of social research is observational, i.e. correlational; we can observe and measure things, ask people questions etc., but it’s not easy to run experiments. This means that often we only have correlational data with which to evaluate and test our causal research questions.
Taken together, the two conditions above present a problem, because as we all know, correlation does not equal causation.
Recently developed theories of causation challenge these limitations. We will use the theory of Directed Acyclic Graphs (DAGs) to understand how causality translates into correlations among variables. We will use this knowledge to help us specify statistical models that may help us evaluate our causal theories.
The statistical models we will use are varieties of Generalized Linear Models (GLMs), specifically Linear Regression and Logistic Regression. We will use the R software package to estimate these models using data. We will evaluate some existing social research studies using our knowledge of DAGs and GLMs.
By the end of the course, students should be able to formulate and understand DAGs that represent hypothesised causal relationships among social phenomena.
The students will then be able to use the DAGs to evaluate which predictor variables they need to include in statistical models designed to answer causal research questions.
The students will be able to use the R software package to estimate two varieties of statistical model, the general linear model (a.k.a. linear regression) and one variety of generalized linear model, binary logistic regression.
The students will be able to use their knowledge of DAGs and the results of the statistical models to answer causal social research questions.
The students will also be able to use their knowledge of DAGs to critically evaluate the results of published studies that used statistical models to answer social research questions.
How the course works
Each week (except the first) I will give you some homework activities (something to read, and/or watch, and/or do). During the following session we will review and explore those activities, to check our understanding. It is imperative that you carry out the homework activities before the session, as the sessions are not lectures as such; they are a chance for us to ask each other questions to check our understanding of the material.
The main session will be held on Thursdays, from 11 AM to 1 PM. This will usually be face-to-face / online teaching from Zochonis Theatre D (or online, if you prefer), but in weeks 5 and 9 it will be online only.
There is a computer practical to complete each week. You can do this from your own PC or if you prefer to use campus facilities then we have booked PC lab 3.59 in Williamson building from 1 PM to 2 PM on Thursdays, right after the lecture. This will be a chance for you to practice using R software by carrying out tasks with support from teaching staff, but note that, to allow for sensible social distancing measures, teaching staff will only be present online, not in the PC lab.
Nick will hold an online office hour on Mondays between 12 – 1 PM, where you can drop in and he will try to answer your questions. You can also post questions to the Blackboard Discussion board before the session.
Amy will hold tutorials on Thursdays between 3 – 4 or 4 – 5 PM. Here you will be going through computer practicals as well as other tasks.
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