This is the repository for Lecture 02 of the Saint Louis University course SOC 4015/5050 - Quantitative Analysis. This lecture introduces core concepts related to data management, data cleaning, and data analysis.
At the end of this lecture and its corresponding assignments, students should be able to:
- Compose a basic R Notebook
- Organize a very simple R project directory with a single subfolder
- Create basic plots using
ggplot2 - Employ
dplyrto carry out basic cleaning of data
- The lecture webpage contains links to resources as well the lecture slides
- The
SETUP.mdfile in thereferences/directory contains a list of packages required for this lecture - The
references/directory also contains other notes on changes to the repository, key topics, terms, data sources, and software. Some of this information is a duplicate of material on the course website. - A starter notebook is included as a base for creating your assignment notebooks moving forward.
Students in my course should clone this repository into their course folder system. Others can quickly download this lecture to their Desktop using usethis:
usethis::use_course("https://github.com/slu-soc5050/lecture-02/archive/master.zip")Students currently enrolled in this course should seek assistance on Slack and/or during in-person office hours before posting questions or reporting possible bugs. Others should see my general policy on support. If you have found a typo or have a suggestion, please check the contribution guidelines guidelines before opening an issue. Please note that contributions to this project are governed by a Contributor Code of Conduct and, for Saint Louis University community members, our various University policies.
Source .tex files for the handouts and assignments for this lecture are available in the extras/ folder. These are intended for instructors who wish to use course materials with attribution and for my students who are moving on to present and teach about these topics.
This course provides an introduction to applied statistical analysis with an emphasis placed on statistical techniques that are most common in the sociological literature. The statistical techniques introduced include measures of central tendency and dispersion as well as measures of bivariate association. Multivariate statistical analyses are also introduced. While the examples may be specific to the social sciences, the theories and skills that are covered are broadly applicable across academic disciplines. More details are available on the course website.
Chris is an urban and medical sociologist with an interest in mixed methods research designs that incorporate spatial data. His dissertation examined the effect of neighborhood context and conditions on emergency medical services work, particularly with patients who have mental illnesses or substance use disorders. He is also part of a research team examining the effects of literacy on mental health service use and recovery, and his student research team is documenting the effects of systemic street closures in St. Louis. He is an Assistant Professor in the Department of Sociology and Anthropology at Saint Louis University. More details are available at his website and he can be contacted at [email protected].
Founded in 1818, Saint Louis University is one of the nation’s oldest and most prestigious Catholic institutions. Rooted in Jesuit values and its pioneering history as the first university west of the Mississippi River, SLU offers nearly 13,000 students a rigorous, transformative education of the whole person. At the core of the University’s diverse community of scholars is SLU’s service-focused mission, which challenges and prepares students to make the world a better, more just place.