2.2 -Analyze Data

Students will be able to analyze data quantitatively and develop testable models of that data:

Being an IB student and having studied pre-calculus in high school gave me the impression that I understood mathematics well when I first started at Longwood. However, learning statistics required a distinct mathematical language to comprehend t-tables and R values.

In Biology 251, we started our journey into quantitative data analysis by doing a lab about the human demographic. Throughout this, we gathered data during the pre and post-1950 human demographic and used the statical application R to further analyze the significance of the data collected.

Requiring to take STATS 171 and 301 allows me to better understand BIOL 341: Ecology and Evolution a lot more efficiently, we learned how to calculate for the t- table in order to get a better understanding of the data collected here for bird diversity. Although we didn’t use the same programming language as the R-study that we did in statics class, my SATs professor always taught us how to gather data from Excel for further cases, so I was well-prepared for my biology classes, such as ecology and evolution. Despite this, even though we didn’t use the same programming language as the R-studio, we still had Excel to gather the same values and data needed to analyze our findings. Overall, completing the prerequisite before taking the higher-level biology courses helped me to better grasp how to interpret R values and determine whether or not data was important. It also helped me get ready for my ecology classes.

I was glad I learned how to use Excel and R in my introductory courses because it was definitely necessary for my upper-level courses. Especially, in my ecology and evolution where we did a lot of data analysis in regards to bird count based on year and seasonal changes.