Beginning Statistical Modeling and Visualization

I have decided to refresh my knowledge of statistics. Despite having taken an introductory statistics class, a sociological research class, an introduction to political science statistics class, and a statistics in sociology class, I find myself remembering very little of the details of the class. Moreover, the only class that used software modeling was the not-required political science class I took that used R, a powerful but less versatile programming language used specifically for statistical analysis. Now, though,  I want to begin using Python.

My hope is that by using Python I will be able to develop my knowledge of the language through practice and be able to transfer that knowledge to other projects. Python is used for a wide-range of applications. It is a general-purpose programming language that is meant to be human readable and has been gradually gaining ground against legacy languages (sort of blue-chip programming languages) like Java and C, for professional applications. (See e.g.https://blog.newrelic.com/2016/08/18/popular-programming-languages-2016-go/). While I do not plan on applying for any CS or coding jobs in the future, I am hoping that Python will have a shorter learning curve than Java or C but will provide me with the opportunity to learn about programming fundamentals and practices.

Applying Python to statistical modeling and visualization will hopefully be immediately applicable to my time in law school. With some diligence and some creativity, I may be able to start applying data visualization to case research: maybe guide my research based on textual analysis. I will need to familiarize myself with JSON, CourtListener’s API, and some beyond-the-basics textual analysis. It should be fun, though, I am looking forward to tackling these projects and, hopefully, carve out a good niche for myself in the legal field.

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