From Data to Science: An Introduction to the National Health and Nutrition Examination Survey (NHANES)

Project Summary

STEM education often presents a very sanitized version of the scientific enterprise. To some extent, this is necessary, but overemphasizing neat-and-tidy results and scripted protocol assignments poses the risk of failing to adequately prepare students for the real-world mess of transforming experimental data into meaningful results. The fundamental aim of this project was to guide students in processing large real-world datasets far beyond their academic comfort zone so as to give them a more realistic understanding of how science works.

Themes and Categories
Paul Bendich

Graduate students: Jameson Clarke and Rick Gawne

Faculty instructor: Fred Nijout

Focus: Questions that can be asked and answered using large public health databases

Skills gained: (I) Accessing and using NHANES, (II) Statistical analyses using JMP

Results: Presentations describing findings and pitfalls of large data exploration

Related Projects

Understanding how to generate, analyze, and work with datasets in the humanities is often a difficult task without learning how to code or program. In humanities centered courses, we often privilege close reading or qualitative analysis over other methods of knowing, but by learning some new quantitative techniques we better prepare the students to tackle new forms of reading. This class will work with the data from the HathiTrust to develop ideas for thinking about how large groups and different discourse communities thought of queens of antiquity like Cleopatra and Dido.

We introduced students to spatial analysis in QGIS and R using location data from two whale species tagged with satellite transmitters. Students were given satellite tracks from five Cuvier’s beaked whales (Ziphius cavirostris) and five short-finned pilot whales (Globicephala macrorhynchus) tagged off the North Carolina coast. Students then used RStudio to calculate two metrics of these species' spatial ranges: home range (where a species spends 95% of its time) and core range (where a species spends 50% of its time). Next, students used QGIS to visualize the data, producing maps that displayed the whales' tracks and their ranges.

This Data Expedition introduces students to network tools and approaches and invites students to consider the relationship(s) between social networks and social imaginaries. Using foundation-funding data that was collected from the The Foundation Directory Online, the Data Expedition enables students to visualize and explore the relationship between networks, social imaginaries, and funding for higher education. The Data Expedition is based on two sets of data. The first set list the grants received by Duke University in 2016 from five foundations: The Bill and Melinda Gates Foundation, Fidelity Charitable Gift Fund, Silicon Valley Community Foundation, The Community Foundation of Western North Carolina, and The Robert Wood Johnson Foundation. The second set lists the names of board members from Duke University and each of these five foundations along with the degree granting institution for their undergraduate education. For the sake of this exercise, the degree granting institutions data was fabricated from a randomized list of the top twenty-five undergraduate institutions.