QSS 20 Modern Statistical Computing Presentations

On November 14, 2022, students presented their final projects for QSS 20, Modern Statistical Computing, a core class in the Program in Quantitative Social Science. Each group of students in QSS 20 selected a data source to investigate, developed a focused research question, and carried out a scientific analysis that applied the programming skills developed through a quarter of dynamic, hands-on learning.

QSS 20 builds on introductory programming skills to equip students with the computing literacy to conduct social science research in the age of big data. The course focuses on learning modern packages for diverse approaches to data manipulation through the flexible language of Python, such as text analysis with nltk and machine learning with scikit-learn. QSS 20 also teaches the foundational computer skills needed in today's computing-intensive environment, including Git/GithubLaTeX; and the command line. 

The course collaborated with the Dartmouth Center for Social Impact and a partner organization, the National Center for START Services (NCSS), to integrate a Social Impact Practicum (SIP) as an option for students' final projects. The SIP allowed students to use their emerging programming skills to promote social good, namely by improving service delivery to and understanding the experiences of individuals with Intellectual and Developmental Disabilities (IDD). Topics ranged from programs for medical students to understand IDD patients, to caregiver experiences throughout the pandemic, to variation in aggression and police encounters across participants' racial groups. Other student groups analyzed sentencing disparities using open data from Cook County, Illinois.

QSS 20 was taught by Postdoctoral Fellow Jaren Haber

These are the student groups, their members, and research questions:

Final project team

Research question(s)


SIP: Training A

Are the learning modules generally effective for improving medical students' understanding of IDD-MH patients? And which specific topics showed the most or least improvement?

Saige Gitlin

Kayla Hamann

Rachael Williams

SIP: Training B

- Are students satisfied with the course?
- Are students mastering the content?
- Of the students who are doing well, what do they like/dislike about the course? What language do they tend to use?

Omario Corral-Williams

Emma Johnson

Max Konzerowsky


- How were caregivers of START patients affected before and after COVID-19?
- How often do START participants exhibit aggressive, self-harming, and other significant behaviors, and how have these changed over time?
- How do trends in Aberrant Behavior Checklist (ABC) scores differ by variables such as race, primary caregiver, and employment status?
- What diagnostic trends are prevalent in START participants before, during, and after the COVID-19 Pandemic?

Andrew Cho

Justin Sapun

Anish Sikhinam

Felony sentencing A

What was the impact of the 2020 Presidential Election on the amount of crime in Washington D.C.?

Luca D'Ambrosio

Filippo de Min

Nick Romans

Felony sentencing B

- Is there a significant difference (if any) in incarceration rates between nonwhite defendants and white defendants?
- How do these differences vary across the city's 25 police districts?
- Does a correlation exist between the demographics of a district and white/nonwhite incarceration rates?

Daniel Céspedes

Giulio Frey

Andy Ilie