Final Project Submission - Vu.docx - #24
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Super cool idea! I like the idea of creating categories for certain teams as “big market” teams. You can use these dummy variables in your regression to see how the betting statistics vary, while accounting for time of game (maybe look at “primetime” vs not). Lots of options for this...initial visualizations may uncover aspects of betting patterns that could be helpful to include in your model.
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This is an interesting topic. My expectation is that bet markets are pretty unbiased, but I may be wrong so it's worth checking. Note that whatever bias you find can be exploited to make profit, so you can imagine it's very tough to beat the bet markets. But give this a shot and we can see together :) |
my 2nd idea for the mini project
committed in wrong folder
2nd idea for mini project
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Interesting idea...I’d be curious to see if there is a relationship between the hand that a player has and the percentage of times they attempt to bluff. Looking at the success rate of certain players would be interesting to see if there are strategies that someone could practice getting better at bluffing. You could also run a regression model to see which in-game factors significantly influence a bluff. Hopefully the webscraping process isn’t too complicated for you to get a variety of variables for your analysis.
The Jupyter notebook file containing the codes to the mini project and a Powerpoint of the results
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Powerpoint for DATA 198 Case Study
duyanhh4
changed the title
Final Project - Data 400
Create Final Project folder
Codebook for the project
cleaned airbnb dataset
Project slides
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Here is the link to our final project submission: https://github.com/duyanhh4/Data400_Spring25/tree/main/Final%20Project |
4 participants
here is my mini project idea 1