Write a blog post explaining what you found. It should answer:
Points 1 and 4 are the most important for the blog post (your analysis document focuses on 2 and 3). This blog post should be aimed at a general audience who is not afraid of graphs/a little data (think 538). The vast majority of the technical details should be in the analysis document.
Include everything that went into creating this plot post in a folder called n_blog (where n = your group number). You can name the blog post whatever you want, just make sure it is a .html document. Please compress n_blog and email it to the instructor.
I plan on posting these blog posts and your analyses on the course webpage. If you do not want your name associated with the post (or if you don’t want even an anonymous version of the post displayed to the outside world) please email the instructor
If you think the final deliverable for your project should be significantly better if is not constrained by the above please reach out to the instructor. For example,
Your project is aimed at a more particular audience (e.g. if you did some fancy machine learning). In this case we might weight your technical analysis more heavily and you can write your blog post for a technical audience.
Your team will get up to 5 extra points on the final project grade if you do the following:
Github pages are very easy to make. The webpage should showoff all aspects of your project including the blog post and technical analysis. The better this page is the more points you will get.