This is the repository of source code and site content for SOC 5050's website. The site is hosted by GitHub.com and powered by Jekyll, an open-source static website generator. The site's original design and source code was produced by Karl Broman and was adapted by Christopher Prener for this class. You can view the site at [http://slu-soc5050.github.io].
Christopher Prener (Ph.D., Northeastern University, 2015) 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 effect of literacy on mental health service use and recovery. 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].
This course provides an introduction to applied statistical analysis for graduate students 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.
Saint Louis University is a Catholic, Jesuit institution that values academic excellence, life-changing research, compassionate health care, and a strong commitment to faith and service. Founded in 1818, the University fosters the intellectual and character development of more than 13,000 students on two campuses in St. Louis and Madrid, Spain. Building on a legacy of nearly 200 years, Saint Louis University continues to move forward with an unwavering commitment to a higher purpose, a greater good.
All code is licensed under a MIT License (see the file LICENSE_CODE.md). The original source code was produced by Karl Broman and is available under a Creative Commons Public Domain 1.0 License (see the file LICENSE_ORIG.md).
All text-based documentation and teaching materials are licensed under a Creative Commons Attribution 4.0 International License (see the file LICENSE_TEXT.md).