Marc Trussler

Marc Trussler

Election Data Scientist

Teaching

PSCI1801: Intro to Inferential Statistics

Undergraduate course, University of Pennsylvania, Program on Opinion Research and Election Studies, 2024

The first step of many data science sequences is to learn a great deal about how to work with individual data sets: cleaning, tidying, merging, describing and visualizing data. These are crucial skills in data analytics, but describing a data set is not our ultimate goal. The ultimate goal of data science is to make inferences about the world based on the small sample of data that we have.

PSCI1800: Intro to Data Science

Undergraduate course, University of Pennsylvania, Program on Opinion Research and Election Studies, 2024

Understanding and interpreting large, quantitative data sets is increasingly central in social science and the business world. Whether one seeks to understand political communication, international trade, inter-group conflict, or a host of other issues, the availability of large quantities of digital data has revolutionized how questions are asked and answered. The ability to quickly and accurately find, collect, manage, and analyze data is now a fundamental skill for quantitative researchers. The answers to a range of important questions lie in publicly available data sets, whether they are election returns, survey results, journalists’ dispatches, or a range of other data types.