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Updated README.md and final-paper.md
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64 changes: 11 additions & 53 deletions Assignments/final-paper.md
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# Project Proposal (10 points)
# Final Paper (40 points)

**Produce a research question and proposal for your term project using a computational social science research design**
**Turn in a formal research paper that uses advanced computational methods to answer a research question by Wednesday, June 12 at 11:59pm. The body of the paper should be no more than 20 pages (1.5 spaced). You may place as much information as you like in an appendix or technical appendix.**


## Elements of a project proposal

1. Clearly state a research question
* Maybe give a few citations (not a full literature review)
* Give a little information about why it is interesting
* Give a little information about what your contribution will be
2. Describe how you will answer that question
* What data will you use?
* Maybe give a preliminary figure/plot/table
* What theory will you use to interpret the data?
* What analyses and computational tools will you use?
3. What do you think your answer might be?
* What are the potential channels and alternatives?


## Proposal format

1. You should prepare a [5 minute quasi-Ignite-style presentation](http:https://www.ignitetalks.io/) using slides
* Exactly **10 slides, auto-advancing every 30 seconds**
* Use any software you want to generate the slides **as long as you include a PDF version**
* Here is a [LaTeX slides template](https://github.com/UC-MACSS/persp-research-econ_Spr19/blob/master/templates/LaTeXslides_template.tex) you can use if you wish.
2. Push your slides to your project repository on your GitHub fork in the `Proposal` folder no later than 11:59pm, Tuesday, April 9.
3. You will present your proposal with slides in class on Wednesday, April 10.


## Things to watch out for

* State your research question clearly
* Usually a narrower scope is better
* Title should refer to a question
* Make sure to use a computationally-enhanced research design
* This could involve computational elements for data collection or statistical learning methods
* This could involve running a digital survey or experiment or simulation
* What you should not prepare - a basic OLS/logistic regression model reevaluating a commonly used observational data set. Do something more computationally cutting edge.
* **Make sure you can get the data**
* If you have a title slide, know that we will spend 30 seconds there
* Manage your time during the presentation
* Don't spend too much time on the literature
* Answer questions but don't get derailed


## How to come up with a good project

* What topic areas are you interested in?
* Read the most current articles.
* Extend one of those papers in a small way.
* New data
* New population
* Question about different part of the data
* New/better methods
* Talk to faculty.
## Grading rubric
1. Did you use appropriate advanced computational methods (10 points)
2. Clarity of research question and convincingness of answer. (10 points)
3. Effective use of visualizations and tables. (10 points)
* Visualizations and tables should stand on their own.
4. Overall paper organization (10 points)
* Did you follow the paper writing advice for each of your sections as given in the course lectures, notes, examples, and slides.
* Structure/flow
* Parsimony and efficiency of language
2 changes: 1 addition & 1 deletion README.md
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| May 29 | W | Effective presentations, poster, slides | [Notes](https://github.com/UC-MACSS/persp-research-econ_Spr19/blob/master/Assignments/poster.md) | |
| Jun 3 | M | Markov and hidden Markov models | [Notebk](Notebooks/Markov/Markov.ipynb) | [PS 4](Assignments/PS4/PS4.pdf) |
| Jun 5 | W | In-class poster presentations | | [Poster](https://github.com/UC-MACSS/persp-research-econ_Spr19/blob/master/Assignments/poster.md) |
| Jun 12 | W | Final papers due at 11:59pm | | Papers due |
| Jun 12 | W | Final papers due at 11:59pm | | [Papers due](https://github.com/UC-MACSS/persp-research-econ_Spr19/blob/master/Assignments/final-paper.md) |


## References and Readings
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