After constructing a simple linear regression that correlates the presence of financial literacy terms with the financial literacy outcomes of speakers from different Indian language groups, I was able to find evidence of a correlation. 

As shown in Figure B, the dependent variable "Terms" is statistically significant (0.014 < 0.05), and the R-squared value is above 0.1. In human behavior research, this correlation is considered acceptable. 

After having done the main analysis, I wanted to analyze different factors that could explain the presence of this correlation. Therefore, I tried to see the effect of sociolinguistic factors such as script type, region, and population density. Script type seemed to have the only significant correlation, which made me think about framing my research from a perspective of digraphia and how that may perpetuate generational poverty. However, I could not find evidence of this after reading different linguistics papers online, and so I needed to decide on a different framework.

I came across the idea of endangered languages and realized that a large portion of the digraphic languages were also either endangered or at risk of endangerment, which provides a much more reasonable explanation as to why speakers of those languages end up struggling more with poverty. 

In conclusion, I would now like to posit my argument connecting endangered languages, literacy, financial literacy, and poverty. This would provide mathematical evidence for existing research in the field, and also provide an area for governments to take action so as to improve the day-to-day lives of their citizens.