2.2-Analyze Data

In high school, I struggled in math because it was so hard for me to understand until I got to calculus. I really enjoyed calculus because it was so different from the normal algebra I had been used to. In college, I was excited to learn more about types of math and how they connect to biology. During freshman year I was accepted into PRISM. We wanted to compare and contrast water quality data and fish data, but to do that with such large data sets we had to use the statistical computing software R. I had to learn how to code in R, make graphs, and tweak the graphs to make them to be what we needed for our final poster project. It was hard and spent so many hours trying to figure it out outside of the time that we were supposed to be working on it. I was very thankful for this opportunity as it set me up to be a driven student for the rest of my college career. Finally, I was able to produce graphs and define the correlation between the two data sets. We found:

  • Lower algal productivity in Briery Creek Lake → Less food available to juvenile bass 
  • Predictive models provide motivation to utilize water quality data in developing fisheries management plans 
  • Academics help bridge data compatibility and communication gaps between government agencies for mutual benefits

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Onto CHEM 350: Quantitative Analysis. I had heard from my peers how hard it was, and boy they were right. I bombed all of the tests, every single last one. No matter how much I studied or how much I paid attention in class. I actually tried everything, I could not even do the homework without going to office hours every single week and trying to do it and asking for help when I inevitably got stuck. I learned a lot from this class. Life does not stop for academic life, ever. You have to preserve through anyways and do the best you can. I worked really hard even though I felt so lost in the class and finally I was able to produce some really good work. My chromatography lab explained the Capsaicin scale. The results were The red dry pepper had a capsaicin concentration wt% of 1.46 and other capsaicinoid concentration wt% of 18.77. The red fresh jalapeño pepper using the Nespresso extraction method had a capsaicin concentration wt% of 0.70 and other capsaicinoid concentration wt% of 16.11. The conclusion of this study was that the dried red pepper had a higher concentration of capsaicin at wt% than the fresh jalapeño peppers. I enjoyed the lab much more than the lecture because the data made me have well-earned pride in my work.

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During my study abroad, we have to synthesize information from both an environmental and economical perspective. The class was called the resource curse of the Amazon rainforest. The Amazon contains so many untapped oil resources, but this is protected land. However, the government has been pushing the boundaries of indigenous land to drill for oil. The future is the entire rainforest being interrupted by roads to drilling access points. My final presentation was after I was able to go and experience this problem firsthand. I think the most important part of this project was to understand the numbers of GPD per capita (Gross Domestic Product) and tourism rates. Then I was able to conclude that oil is a dying and unstainable resource for cash flow but prioritizing tourism which can provide endless income. Overall, statistics and data analysis are imperative to concluding statistically significant findings within the biological field of study. They are important because they provide proof of why sharing, comparing, and understanding the biological implications of the research.