Three (p)refresher workshops for graduate students
August 23 to 25, August 28 to 30, and August 31
Faculty Advisors: Aaron Erlich (Political Science) and Thomas Soehl (Sociology)
Quantitative approaches comprise a large and growing part of social science and humanities research. It is increasingly difficult to take graduate level courses and read important papers in your field without an understanding of statistical inference, computer programming, and mathematical models. McGill offers a wide range of courses to give you competency in these areas, but sometimes graduate students feel inadequately prepared to take advantage of these resources. To help you make the most of your studies, the Faculty of Arts in collaboration with the Centre for Social and Cultural Data Science (CSCDS), the Centre for the Study of Democratic Citizenship (CSDC), the Geographic Information Centre (GIC), and the Departments of Political Science and Sociology offer three workshops before the beginning of fall term. The workshops assume no background!
We encourage you to take all of the workshops, particularly if you are an incoming graduate student, but you can also register for only one workshop. Detailed outlines of each syllabus will be available later in the summer.
Workshop I: Review of basic mathematical and statistical concepts.
Instructor: Costin Ciobanu [4 days (day 1 optional) – Tuesday, August 21 to Friday, August 24]
This workshop will (re-) introduce you to notation commonly used in statistics, cover functions, basic calculus, probability theory, and linear algebra.
Day 1 (Optional): Review of basic Algebra, functions, notation (Greek leÄers)
Day 2: Basic Probability
Day 3: Calculus: Func.ons, deriva.ves, integrals
Day 4: Linear Algebra: Vectors, matrices, matrix mul.plica.on, determinants
Workshop II: Introduction to statistical computing in R, and typesekng languages.
Instructor: Tim Elrick [4 days – Monday, August 27 to Thursday, August 30]
This workshop will introduce you to R, a common statistical programming language used across many courses at McGill as well as rmarkdown (typesekng language useful for producing documents that contain mathematical content and code). These are very useful and powerful tools but they have somewhat of a steep learning curve. So the goal of this part of the workshop is to get you up a good part of that learning curve.
Day 1: Introduction to R and working with data in R
Day 2: Cleaning data, types of variables and lists, dealing with missing data
Day 3: Descriptive Statistics, creating graphs using ggplot2
Day 4: Typesekng using R markdown, R-studio Add-Ins
Workshop III: Introduction to replicable research using version control.
Instructor: Aaron Erlich [1 day – Friday, August 31]
This workshop will introduce you to Git and Github to manage your research projects. Git and Github allow for easy collaboration. They also allow you to generate replicable files necessary for publication in many journals.
NONE! If you never heard of these topics you should not be scared off. In fact, you are the perfect student for this workshop. The goal is to give you a basic overview of the material as well as the resources and the confidence to learn more. If you already have some background, but have not used this material recently, these workshops will also be useful.
The workshops are free to attend for all McGill students and members of the CSDC. In fact, budget permitting, we will provide free coffee and potentially lunch. If demand exceeds capacity, we will give preference to incoming graduate students. We will start forming the courses in early August. To be guaranteed consideration register before July 31 at this link :
Sponsored by: Faculty of Arts, CSCDS, CSDC, GIC, and Departments of Political Science and Sociology
The workshops will run all day from 9am to 4pm with a one hour lunch break. These workshops are not for credit and there are no exams. Nobody but you will know how well you did. Still, taking the workshop will require a commitment. We expect you attend the en.re sessions, do any readings we assign and participate in all aspects. The format will involve a mix of lecture and hands-on practice. Just like any skill, you can’t learn math and computing by just watching. You have to do it to learn it.