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r/PhilosophyofScience
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r/cscareerquestions
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CSCareerQuestions protests in solidarity with the developers who make third party reddit apps. reddit's new API changes kill third party apps that offer accessibility features, mod tools, and other features not found in the first party app. More importantly however, the behavior of reddit leadership in implementing these changes has been reprehensible. This sub will be private for at least a week from June 12th. For more info go to /r/Save3rdPartyApps/ ​ https://redd.it/144f6xm/
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r/cryptography
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For people interested in the mathematical and theoretical side of modern cryptography.
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r/ScienceArticles
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Welcome to r/ScienceArticles
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A Subreddit for Quality Educational Documentary Videos covering Mathematics and Science
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r/allscience
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Welcome to r/allscience
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r/REMath
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Computer code is a complex logical artifact and high dimensional dynamical system whose extension, maintenance, comprehension, and verification is difficult but can be made easier by creating tools that aid humans in these domains. This subreddit is for people that want advance the field of machine language processing by working to advance ideas to help humans understand computer code of all types and sizes.
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A moderated community dedicated to all things reverse engineering.
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A subreddit for the discussion of possible living ground sloths, and for ground sloths in general.
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r/Labour
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A subreddit for the Left of the UK Labour Party (Momentum/LLA/Socialist Appeal/LRC/etc), the wider Labour/Union movement, and Socialism within the UK, including other socialist parties.
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r/outsidetheparadigm
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This is a subreddit to discuss big-picture notions of scientific paradigm change. Realistically and historically-speaking, how do new ideas and new theories become part of mainstream science? Are scientists exceedingly close-minded, or is the conservatism of science an essential aspect of its methodology? How can paradigms ever change if professional scientists are only trained to think within the mainstream paradigm?
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This is a subreddit for economics discussions grounded in careful research, getting help with finding papers on a certain topic, or for simply sharing economics papers that we enjoy.
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r/AskAcademiaUK
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For questions about academia specific to the United Kingdom. /r/AskAcademia is a helpful resource for finding out more about academic life, pathways into and within academia, and other general questions, it is very often centred around US based academia and therefore not always relevant outside of the US. This subreddit will therefore function as a counterpart to /r/AskAcademia, one that is specific to UK based professional academic life. WE SUPPORT THE USE OF OLD REDDIT - Please see sidebar.
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r/BeyondDebate
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Welcome to /r/BeyondDebate, the subreddit for harvesting information by analyzing debates while exploring the nuts and bolts of applied logic and critical thinking.
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Posted by9 days ago
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Posted by1 month ago

After seeing u/wormhole222's post highlighting the fact that, despite being currently up 2-0, ESPN only gives the Heat a 35% of winning their series against the Celtics, I decided to do some investigation, and I think I figured out why this model is so risibly fallacious. I believe that, at the start of the playoffs, they created a set of probability values P for each team winning a single game against each other team and from that extrapolate performance for the entire playoffs. My evidence is as follows.

At 0-0, they gave the Heat a 3.2% chance of winning their series. If they are deriving this value in the way I believe, then it can be found by solving the equation Σn=47 (pn )(1-p)n-4 (n-1 choose n-4) = 0.032, or as written out, the 7th degree polynomial p4 +4 * p4 * (1-p)+10 * (p4 ) * (1-p)2 + 20 * (p4 )(1-p)3 = 0.032. This has one real solution in the interval [0, 1], 0.197625, so from this we can assume that ESPN's model gives the Heat around a 20% chance of winning any given game against the Celtics.

How can we test this hypothesis to see if it's true? The Heat are now up 2-0 against them, and ESPN now gives them a 35% chance of winning the series. We can calculate the probability of a team winning two games before its opponent wins 4 given a constant probability value for it winning a single game. The formula for this is 1-(3*(1-p)4 (p)+(1-p)4 ), and sure enough when you plug in p=0.2, this expression evaluates to 0.344, a 34.4% chance of winning, very close to ESPN's assigned value and within the margin of error for their reported significant figures.

In effect, ESPN has taken the laziest approach for statistical modeling and run with it. This approach can work for simplistic systems and would be fine if basketball tournaments were a fixed Markov process, but they are not. They are not updating probabilities for individual game victories based on team's recent performances, especially in head-to-head matchups. More complex analysis would also factor in game location, as the NBA has demonstrable home court advantages, and could also draw on historical trends from series results given the current record to try to capture the concept of momentum.

As it is, in the same way their reporting, talking heads, and game broadcasts are often subpar, so too is their statistical modeling and it shouldn't be used for any realistic assessment of a team's playoff odds.

EDIT Woke up this morning, saw this had blown up, and decided to spend more than the 5 minutes this initial shitpost took to gather additional data, particularly as spurred on by a few commenters pointing out that my results were not consistent with the odds given after game 1. I no longer believe that ESPN is modeling their playoff odds as a fixed Markov process, and chalk my original conclusion up to a remarkable coincidence in the data.

That being said, I still fervently believe they put as much effort into developing things like this as they do with the rest of their product, namely not much. I think that they need something with a higher update velocity to better account for playoff momentum, and I do not believe they are giving historical outcomes of teams up 2-0 in a series enough weight.

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