In this assignment, students will generate an original informational report built on a data set of their choosing from NYC Open Data. This is the open data repository for the City of New York.
Students will create a blog post that delivers a useful informational product to a definable audience of their choosing. The analysis should use data distributed through NYC Open Data, and serve an audience whose practical interests are related to whatever is measured in the data. The post should be between 800 – 1500 words, and include at least one visualization.
Your report should follow this outline:
- Abstract: In 50 words or less, summarize the entirety of the article
- Introduction: Begin with a very direct and concise strategy of your analysis, its findings, and the insights or uses of these findings. Begin your report by summarize it in its entirety in the first paragraph. In the second paragraph, provide an outline and brief preview of the paper. Optionally, you can try to begin this section with a lead paragraph that hooks or set up the piece. (approx. 150 words)
- Background: Give the reader background information to understand the analysis and its uses. You might consider discussing topics like: Who will use this piece of information? How will they use this information? Which beliefs, decisions, or practical actions does your analysis probe or inform? What have other people said on this topic, and how might your analysis contribute to the discussion? What theoretical concepts or relationships are implicit in the beliefs that you engage? These types of questions help your audience understand the meaning and stakes of your project.
- Data and Methods: Which data did you use? Whom or what does the data measure? Which variables are the focus of your analysis? What are these variables supposed to measure? What information are you trying to extract from this data? What is the appropriate operation for performing this analysis, given your goals and data? Should the audience be aware of issues with the data or analysis that would influence efforts to make sense of and replicate the analysis?
- Analytical Results: This section provides key information extracted from the data, so that the audience can see the details of your findings and lines of reasoning. Topics here might include univariate statistics, bivariate statistics, inferential statistics, data visualizations, regression models, multivariate analyses, data reduction operations, and other topics taught in this class and throughout the Analytics curriculum.
- Conclusion: Summarize the empirical findings and their meaning. Help the reader understand everything that they saw over the course of your research report, and what conclusions they should take away from this read. This is a place where you can discuss future directions or some other closing item.
Please email to me (firstname.lastname@example.org) in a zip file with your last name and “712-1” in its name (e.g., “712-1 Cohen.zip”):
- Your Markdown file
- A copy of the data that you used
- A Word document with a polished version of your report.
All submissions should adhere to the class’s General Assignment Guidelines.
Due date is Wednesday, February 28, 2024
To see an example of a submission that I created, check out this post on restaurant violations in NYC restaurants.
- To consolidate basic skills in R through an applied exercise
- To introduce students to the City’s open data infrastructure
- To create a writing sample that the student can use to showcase their work
- Students will receive extra credit if their project is published in the NYC Open Data Project Gallery and/or the QC DataBlog (in development).
- If you are interested in City data, you might enjoy NYC Open Data Week, which will be this March 16 – 24. QC Data Analytics students have presented at that conference in the past.
- Keep up to date with NYC Open Data by signing up for their email list.