Directions: Please read the directions below carefully. If you have questions, please reach out to Prof. Hooper for clarification.
I hope you enjoy working on this project. I also hope it will not take too much of your time as preparing for final exams and keeping up with your other courses should be a higher priority. Please contact Prof. Hooper if you have concerns about completing your final project.
By: Insert your name here.
Please describe your data source(s). Explain what information is in the data source, highlighting the information you use. If your data source was downloaded from a website, then include the website's address. Also explain what interests you about this data source. Citations can be added to the Citation section below and cited by number, e.g. .
Explain what you accomplish in this notebook. This can be a sort of introduction. You do not need to layout lofty goals. Keep the goals limited to what you actually accomplish in this notebook.
Include and document code which makes the data in your data source available for use by Python.
Include and document code which analyzes the data and achieves the goals laid out above. Be sure to cite sources, even if you just based some of your code on code available online. Clearly indicate what portions of the code are purely your own, so that it is clear you did a substantial calculation on your own.
Explain why your analysis accomplishes what you laid out in the Goals section. Explain the significance of what you found. Such an explanation might just say that your results are inconclusive (which is a common outcome in real research) or that your analysis was not rigorous enough to conclude anything.
Explain what if anything you learned from this project. This can be things related to this course, other things you learned in the course of doing this project, or things you learned from the analysis of the data.
Explain what you would try to do in the future if you were to continue analyzing related data.
Data source. An appropriate data source was used. The information contained in the data was clearly explained. The data source was clearly cited. Motivation for looking at this data was provided. (10 points)
Goals. Goals for this notebook were clearly laid out. Goals were limited to what is reasonable to achieve. (10 points)
Importing Data. The data was successfully imported into Python from a file or website. The importing of the data was repeatable when the notebook was run from scratch. (In particular, if the data source is a file, then that file must be turned in with this final project notebook.) (20 points)
Analyzing Data 1. Code in the data analysis section was clearly written and well documented. Sources used were clearly cited. The calculation is repeatable by rerunning the notebook from scratch. (10 points)
Analyzing Data 2. A substantial calculation was carried out utilizing ideas from this course. This calculation was clearly marked to be the student's own work (possibly with assistance from the course website and textbooks). This calculation is repeatable by rerunning he notebook. (30 points)
Analyzing Data 3. The analysis was as complete as reasonably possible. That is, it would take more than a relatively minor effort to substantially improve the analysis provided in the direction laid out in the Goals section. (5 points)
Conclusion. The conclusion adequately justifies that the goals were accomplished. The significance of the analysis was correctly analyzed. (10 points)
Citations. Citations are complete, clear, and written in a consistent style. It is possible to find the sources using the citations. Citations are included inline as appropriate throughout the document. (You might include “” to cite reference number 5 inline.) (5 points)
Reflection. A discussion of what was learned in carrying out the project was included and appears reasonable and complete. The discussion what further analysis might be done is reasonable and interesting. (10 points)