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- | ====Objective:==== | ||
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- | To creatively apply knowledge gained through the course of the semester to a substantial data science problem. | ||
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- | ---- | ||
- | ====Deliverable:==== | ||
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- | You must turn in a PDF writeup of your project. The writeup must be about 6 pages long (including figures). | ||
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- | ---- | ||
- | ====Grading standards:==== | ||
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- | Your final project counts as about 15% of your overall grade (see Learning Suite for a precise breakdown of the value of different assignments). | ||
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- | I will evaluate your writeup primarily based on the quality of your writing. Grades will be derived approximately as follows: | ||
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- | * 10% a clean introduction and summary of findings | ||
- | * 80% the main technical sections | ||
- | * 10% conclusion - lessons learned, etc. | ||
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- | **Note that no late submissions are possible for this project, because it is done in lieu of the final exam.** | ||
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- | ---- | ||
- | ====Dataset:==== | ||
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- | For your final project, you must analyze the ANES dataset used in class. As a reminder, this dataset captures the political landscape of 2016, and includes a wide variety of demographic and political variables. | ||
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- | The dataset is available at | ||
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- | [[http://liftothers.org/byu/anes2016.csv]] | ||
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- | and the codebook is available at: | ||
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- | [[http://liftothers.org/byu/anes_codebook.pdf]] | ||
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- | For more information about the ANES, you may also visit their official website: | ||
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- | [[https://electionstudies.org/data-center/2016-time-series-study/]] | ||
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- | ---- | ||
- | ====Description:==== | ||
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- | For your project, I expect you to produce a significant report that leverages the skills and concepts we have learned in class. Your final report must be structured as follows: | ||
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- | * Introduction - summarize interesting insights you uncovered | ||
- | * At least six technical sections - one for each substantial analytic effort | ||
- | * Conclusion - what did you learn as you analyzed this data set? | ||
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- | You may include more technical sections if you would like, and your may be more than 6 pages long (but not less). | ||
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- | Each technical section must contain | ||
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- | * A sentence or two describing what you set out to do | ||
- | * Some technical detail on your approach | ||
- | * Some sort of visualization of the result (a figure, a table, etc). | ||
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- | I expect each technical section to be about 3/4 - 1 page long, although it could be longer. You may, of course, include multiple visualizations for each section -- whatever conveys insight! | ||
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- | ---- | ||
- | ====Possible ideas for elements of your project:==== | ||
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- | The ANES dataset is large and complex. Many different kinds of analysis and visualization are possible. A few examples include: | ||
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- | * Looking at correlations between different variables | ||
- | * Comparing marginal and conditional probabilities | ||
- | * Visualizing histograms (or KDE plots) of different factors | ||
- | * Clustering ANES individuals based on different factors (and/or distance measures) | ||
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- | ---- | ||
- | ====Notes:==== | ||
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- | You are welcome to use any publicly available code on the internet to help you. | ||
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