Katie McMahon is one of three GSIs working in this year’s brand new QMSS 301 course. Katie hails from Midland, Michigan and completed her undergraduate degree in biology, ecology, and evolution at Central Michigan University. Here at U of M, she is now working towards her master’s degree in the SEAS program (School of Environment and Sustainability) and is focusing specifically on environmental policy and environmental justice. After her undergraduate studies, Katie briefly worked in marine biology but was motivated to pursue a career in environmental policy after seeing the major effects of climate change on the oceans.
Katie is relatively new to the QMSS field, but her background in science has provided her with many skills equipping her to be a valuable GSI for the 301 class. In the past she has completed a lot of work in biostatistics and natural resource statistics. Through this, she became well-acquainted with various computing programs, especially R and Excel. While she has studied a lot of “hard-science” in the past, Katie is excited to learn more about social science and get to look at data through a new lens. Her desire to learn these things prompted her to branch out from teaching conservation biology and pursue working as a QMSS GSI. Katie attests that “the best way to learn something is through teaching.”
The research Katie is involved in at U of M centers on environmental policy and justice.
Her Masters project focuses on getting building owners in Detroit’s 2030 district to commit to lowering their emissions by 2023. For this project she analyzes large survey datasets and works with GIS mapping software. The objective of this project is to make Detroit more environmentally friendly, thus improving the city.
Katie believes that a QMSS education is beneficial for all students. The 301 course, specifically, teaches students to understand data and think critically. She believes it’s incredibly important to be able to draw your own conclusions from data, rather than simply taking someone else’s assessment of it. One of the first QMSS 301 projects focused on doing exactly that and allows students to see how data is frequently misconstrued. She also believes the QMSS curriculum puts students at a great advantage going into the modern workforce because they will know how to use computing to understand the ever-increasing amount of data in the world.
Katie has really enjoyed working as a GSI for QMSS 301 so far. She has found it especially rewarding to help build lessons and projects for this course as a part of the pilot team. She enjoys that the course includes many guest speakers who provide important perspectives and career advice for students. A 301 project that she finds particularly interesting uses logistic regression to predict outcomes of sporting events based on player salaries then compares predictions to actual results. Overall, Katie is very excited to explore QMSS with the 301 students this winter.
