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

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Matt and Ken led two labs for the engineering section of STA 111/130, an introductory course in statistics and probability. The lab assignments were written by Matt and Ken in order to bridge the gap between introductory linear regression, which is often explained in terms of a static, complete dataset, and time series analysis, which is not a common topic in introductory courses. 

Graduate Students: Kendra Kaiser and John Mallard

Faculty: Michael O’Driscoll

Course: Landscape Hydrology, EOS 323/723