Amelia McNamara

Photo courtesy Jim Gipe

Amelia McNamara

Smith College Visiting Assistant Professor of Statistical & Data Sciences, MassMutual Faculty Fellow.

Statistics PhD from the University of California, Los Angeles.

My work is focused on creating better tools for novices to use for data analysis. I have a theory about what the future of statistical programming should look like, and am working on next steps toward those tools. For more, see my dissertation.

My dissertation was officially co-advised by Rob Gould and Rick Schoenberg, although I worked closely with Mark Hansen for many years. As a graduate student, I also worked with with the Viewpoints Research Institute (VPRI), directed by Alan Kay (another member of my dissertation committee). A full list of my committee members and abstract of my dissertation is available here. Towards my vision of statistical programming, I worked with Aran Lunzer at VPRI to explore the effects of aggregation on data, both in one dimension (histograms) and in two dimensions (spatial patterns).

My research interests include statistics education, statistical computing, data visualization, and spatial statistics. In Spring 2016, I directed a group of research students on an independent project related to spatial statistics, the change of support problem, and the Modifiable Areal Unit Problem. I am always willing to work with students on research projects, so whether you have something in mind already or want to work on one of my current projects, please let me know.

Over the years, my educational career has included elements typically associated with the right brain (design foundations, college English major) as well as the left brain (math was my other undergraduate major, and my PhD is in statistics with a focus on computation).

However, I dislike the tendency to pigeonhole projects and people by the dichotomy of the right and left brain. Instead, I prefer to focus on projects that use a more holistic approach. In both my research and my teaching, I try to balance quantitative rigor with excellent communication.


Research

For a more detailed look at my recent work, see my writings and presentations, or look at some of my other recent projects. Or, look at my dissertation committee members and dissertation abstract, and read my theory about the future of statistical programming.

Teaching

At Smith, I am teaching Multiple Regression for the second time (first in Spring 2016, now Fall 2016). In Fall 2015, I taught Introduction to Probability and Statistics, which I will teach again in Spring 2017.

As a graduate student at UCLA, I had the opportunity to develop and teach a data visualization course. I was given the opportunity to develop this course as part of the Collegium of University Teaching Fellows program at UCLA. During my time at UCLA, I also served as a Teaching Fellow. I taught discussion sections for three upper-division statistics classes (101a, 102b and 101c).

For three years, I was also a graduate student researcher on the Mobilize project, which brings data science to high school students in the LA area. The curriculum includes participatory sensing and computational analysis in R and RStudio. My work with Mobilize is discussed here, and has been a source of inspiration for my ongoing research into computational tools for novices.

Curriculum vitae

My CV is available here, and if you're curious about how I TeXed it up, view the code.

 

Contact me

Reach out to me electronically:

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