Encouragement for Novice Coders: You've Got This!
At Princeton University, one student is making a significant leap from law to coding as they embark on writing their SPIA Quantitative Junior Paper. This transformation began when they decided to tackle the PSET for the statistics course, POL 345: Statistical Methods in Political Science.
Initially, the student was apprehensive about coding, having heard negative rumours about math and computer science courses at Princeton. However, they found solace in the accessibility of POL 345, a course designed for first-time coders who want to apply code to a policy context.
The student approached the PSET with determination, making use of precept assignments, lecture notes, office hours, and the McGraw Center. Their efforts paid off, as they found the content of the first PSET both interesting and understandable.
The student's choice to take POL 345 was strategic, as it counts as the SPIA statistics prerequisite and offers a great way to learn how to code. They found enjoyment in using R for statistical computation, a skill that is increasingly valuable in policy research.
Princeton University offers a range of policy-relevant introductory statistics courses. For those seeking a more coding-heavy approach, courses like ORF 245: Introduction to Stochastic Systems or SML 201: Statistical Methods in Molecular Biology and Public Policy may be beneficial.
It's worth noting that another student, Ryan Champeau, took a statistics course for their major that required coding. This demonstrates the versatility of these courses, catering to students from various backgrounds and academic interests.
In conclusion, for a first-time coder focused on policy at Princeton, POL 345: Statistical Methods in Political Science is a highly recommended introductory statistics course. It provides a blend of statistics, policy applications, and accessible coding/statistical software training, setting students up for success in their academic pursuits.
In their pursuit of writing the SPIA Quantitative Junior Paper, the student is not only studying data-and-cloud-computing to code their project, but they are also applying this newfound technology skill in the context of education-and-self-development, specifically through the lens of policy research. As they progress, they might find other courses like ORF 245: Introduction to Stochastic Systems or SML 241: Statistical Methods in Molecular Biology and Public Policy useful for further learning and expanding their junior paper to include more data-centric policies.
