Statistical Consulting for Kinesiology Capstone Projects

Faculty Sponsor

Kelly Helm


Arts and Sciences


Data Science, Kinesiology

ORCID Identifier(s)


Presentation Type

Oral Presentation

Symposium Date

Spring 4-29-2021


This project explored the application of data science techniques to kinesiology research initiatives led by students. Statistical analysis is becoming increasingly popular in academic research due to the ease of use provided by modern technology. As a result, the field of data science is growing and its relevance in education is becoming more prominent. This project will explore the relevance of data science principles in a program of higher education.

To investigate this, I consulted 17 senior kinesiology students in their capstone project course. Each project collected its own data with which I was able to provide statistical insights to the relationship being studied. From these explorations I observed which data science techniques appeared most frequently in results production. I worked with each student to clean their data, perform statistical tests, and make meaningful conclusions from the numbers.

Many of the same techniques were used between projects despite their methodologies being completely different. Among the most common were procedures taught in introductory statistics courses. In particular, the Repeated Measures ANOVA was utilized to answer multiple research questions. These results indicate that real research questions are related in what techniques they require. This knowledge allows us to more effectively incorporate relevant research practices into a program’s course track.

Biographical Information about Author(s)

I am personally interested in the applications of Data Science principles in academic research. Because of this I joined the Kinesiology Department's senior research class to test my abilities in an unfamiliar subject area.

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