Students will be able to analyze data quantitatively and develop testable models of that data.
One of the first research projects I worked on at Longwood University was for a class called Introduction to Ecology and Evolution. For this project, I collected data from a local cemetery with the goal of identifying and describing any trends. The results of this project can be seen in a paper I wrote describing the male to female ratio of those buried at the cemetery and their average age of death. Because this was one of my first research projects, this was also my first time trying to interpret and analyze data. This was obviously out of my wheelhouse at the time since I chose to look at the most basic trends possible and thus came to some very basic conclusions. I have since become much better at interpreting and analyzing data, but I think that this project was helpful for me nonetheless. Even though I wasn’t very ambitious and my conclusions were nowhere near groundbreaking, it gave me the exposure and experience I needed to really improve upon this particular set of skills.
I was a bit more ambitious in a research project I took part in later on in a class called Comprehensive Human Anatomy and Physiology I. For this project, we decided to investigate the effects of load carriage on the posture of college students. We collected preliminary data that showed us the average weight of a student’s backpack and went from there, going on to show the effects of that weight on posture and heart rate. By the end, we had collected 1,200 data points for body angles alone in order to assess changes in posture. The results of this project can be seen in a poster presentation I gave. This project not only involved a lot of thought and planning in order to collect the data but a much more in-depth analysis of that data as well. The contrast between both the process and the end result of this project and the one mentioned previously is extremely apparent and I think this demonstrates my increased confidence and improved ability to interpret and analyze data.
The culmination of this skill can really be seen through my work on a research project for a class called Comparative Biomechanics. For this project, we investigated the effects of limb loss on stinkbug locomotion. The results of this project can be seen in a presentation I gave at the end of the class. For me, this project involved a lot of data analysis from start to finish. As a part of an independent research project that I was working on to help collect the data for this class, I had to train an AI program to recognize and trace stinkbugs in videos, which relied on constant data analysis to assess accuracy. For example, we had to constantly check the p-values of the data being produced during tracking to assess the confidence of the AI in locating certain points on the bug. The program gave us way more data than we could have used, so to prove our hypotheses really meant demonstrating our skills in terms of evaluating and interpreting the data.
Data analysis is crucial part of any experiment so knowing how to accurately interpret and analyze your data is a necessary skill to have, especially if you plan on going on to do laboratory research. I am glad to have had the opportunity to practice data analysis in a number of different settings and contexts throughout my time here at Longwood.