Editing Community Data Science Course (Spring 2015)
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==== Paper and Code ==== | ==== Paper and Code ==== | ||
Your final project should include | Your final project should include details information on: | ||
* The problem or area you have identified and enough background to understand the | * The problem or area you have identified and enough background to understand the work that follows. | ||
* Your research question(s) and/or hypotheses. | * Your research question(s) and/or hypotheses. | ||
* | * Your methods, data, and approach that you used to collect the data plus information on why you think this was appropriate. | ||
* | * Your results including numbers, tables, and graphics and figures. | ||
* A discussion of limitations for your work | * A discussion of limitations for your work. | ||
If you want inspiration for how people use data science to communicate | If you want inspiration for how people use data science to communicate findings broadly and effectively, take a look at great sources of data journalism including [http://fivethirtyeight.com/ Five Thirty Eight] or [http://www.nytimes.com/upshot/ The Upshot at the New York Times]. Both of these publish an large amount of excellent examples of data analysis and a bit of it is actually done using Python and web APIs! A simple Five Thirty Eight story will include a clear question, a brief overview of the data sources and method, a figure or two plus a paragraph or two walking through the answer, and a nice conclusion. I'm asking you to produced roughtly like. | ||
Keep in mind that most | Keep in mind that most story on | ||
You should also share with me the full Python source code you used to collect the data and the dataset itself. | |||
I will not be judging the quality or quantity of your code but rather the degree to which you have been successful at answering the ''substantive'' questions you have identified. | |||
==== Presentation ==== | ==== Presentation ==== |