I decided to write a data-based IA, mostly because I could apply my findings to the real world. From growing up in countries with heavy smog, I knew I wanted to focus on air pollution. Instead of focusing on the molecules causing pollution themselves (which would be closer to studying chemistry), I connected air pollution to a specific lung disease.
In many ways, my IA was simply an extension or question on a connection that I already had in my mind. To me, air pollution and the lungs came hand-in-hand; it was simply a matter of seeing the numbers to understand this relationship. It may help to just think about what made you interested in the subject matter, and explore a small portion that can fit onto 12 pages. This may not be in the shape of a data-based IA but may be a lab-based experiment. Both ways, start thinking about your topic early on. Before I decided on my topic, I felt overwhelmed, especially because I did not know how to conduct statistical tests or a proper lab experiment because of the pandemic. If you are feeling overwhelmed, start researching past experiments or look through your study notes. Although you may feel tempted to gravitate towards popular experiments, do add your own twist to your investigations!
Although data collection took an hour or two, organizing the numbers took many more. From graphing standard deviations to computing a statistical test, I spent a few afternoons making sense of the data. Do start early, as even the portions that are less analytical can take up a lot of time. The analysis portion took an overwhelming majority of the time, which can get tiring. Regardless, the heavy emphasis on the analysis section in my IA helped me reflect on the weaknesses of and improvements for my investigation — do mention these in your evaluation, as well as analyze their significance. It may seem intimidating, but if you trust the process and think through every step, the ideas will come naturally.
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