4 ms·

Hi there, "OP" here. First off, it's been fun to see this post spread across the interwebs since I first wrote it one caffeine-fueled day just over a week ago

by JmsPae 2y ago

Hi there, "OP" here. First off, it's been fun to see this post spread across the interwebs since I first wrote it one caffeine-fueled day just over a week ago (first Menéame, now here) and for the heck of it, I thought I would clarify a few things; This post was (sortof) a meme. Sure, I "understood the assignment" and performed the quick "study" ("analysis" might be more fitting) for the sake of the original post over on r/gis, but I was surprised to see how seriously others took the matter. I suppose good kebabs are a serious matter. As others have pointed out, a linear correlation was likely a flawed approach for testing the "hypothesis". Though the original wording from the french post which first brought this to my attention implied as much, in hindsight it's likely that the kebab shops within a certain radius are on average worse than the rest. Also, it seemed that Paris was one of the worse study areas. It, apparently, has some very good kebab shops that just so happen to be in close proximity to train stations. I suppose I need to start working on part 2....

dr_kiszonka 2y ago
Try fitting something non-linear or simply plot a mean (or median) rating over distance with some smoothing.
wjholden 2y ago
Which R-Tree Rust library were you referring to?
- JmsPae 2y ago
  https://github.com/georust/rstar https://github.com/georust/rstar Banger library. Not sure how it compares to, say, kd-tree in terms of performance but it allows for plenty of primitives.
lqet 2y ago
Why did you include metro stations in your study? The original quote only included train stations. The metro originally largely replaced a tram network, so the metro station density in Paris is higher than for other underground systems. I think it is very hard to find kebap shops in Paris that are not within 500 m of a metro station. This kind of dilutes the significance of your study, because I never really noticed that metro stations had a negative impact on their surrounding area (the opposite, really). I think your study would have been much more interesting (but not that algorithmically challenging...) if you only included the large train stations in Paris.
- maeln 2y ago
  I would second this. In Paris, but I find it to be true in most European city, the area surrounding train station is usually not very nice. It is usually surrounded by cheap hotel for 1-night traveler, overpriced fast food (hence the initial theory) and social housing / cheap building (a lot of people don't want to live next to a train station due to the nuisance, so poor people often get stuck there). On the other hand, metro station are pretty much anywhere, and they tend to have the opposite effect. Having a metro station close by is very practical and doesn't generate as much nuisance since it is underground and pretty well hidden. I am almost sure the data will look very different if you only look for train station.
  - yard2010 2y ago
    This is such a dystopian phenomenon, I'm far from an expert but I guess it's a matter of city planning?
    - lqet 2y ago
      It's very hard to avoid this. It's mostly a combination of railway noise, throughput of a large number of people who are only travelling through, opportunities for pickpockets and beggars, and historically of soot and air pollution by steam engines, which makes these areas unattractive to live in. And it is not for lack of trying. City planners since at least the 1850ies have been trying to improve the areas surrounding large train stations.
      - Symbiote 2y ago
        It's also a very large building or roofed space, where it's more difficult than elsewhere to accuse homeless etc of loitering.
    - Beretta_Vexee 2y ago
      It is difficult to avoid, as metro passengers are mainly residents or workers in nearby premises. Station halls are also much bigger and attract the marginalised who want to shelter from the elements.
randomcarbloke 2y ago
please do berlin, london, and stockholm.
- vanderZwan 2y ago
  Yeah, this is a nice selection of European cities to compare! Having lived in Berlin and Stockholm (and a few other cities), I'd say Stockholm has by far the worst kebab options of all places I've lived, while Berlin was the best one. I'm curious whether this is reflected in local reviews, or whether the locals just lower or heighten their standards based on the what the average food quality is like.
  - vidarh 2y ago
    Kebabs are one of the foods (like Chinese cuisine) that morphs depending on a combination of which kebab-eating group brought it to the country, and local cuisine. I'm not sure about Stockholm, or Sweden in general, when it comes to kebabs, but kebabs in Norway bear little resemblance to the kebabs I get in London. And the UK now has a chain serving "German" kebabs, which again are significantly different from the kebabs we get from Turkish takeaway places and restaurants here... It's not that they're better or worse - I might crave one or the other depending on what I'm in the mood for, as they're almost different dishes. So, comparing cities against each other is a lot harder than comparing differences in local opinion by location within a city.
    - phist_mcgee 2y ago
      Kebabs in Australia are basically a different food to the one you get in continental Europe. Good, but different.
    - randomcarbloke 2y ago
      The author is Swedish, and having asked some Swedes they basically consider the kebab to be the goto "local" cuisine. London of course has the two styles, |Turkish| and Turkish via Germany.
  - ido 2y ago
percevalve 2y ago
That looks like a typical collider bias to me... There should be no correlation between location and quality... But as you are looking at restaurant that are still "in business" you are introducing a bias. If you simplify, a restaurant can have : - good/bad location - good/bad food If your restaurant has bad location and bad food, it is not going to stay in business very long. After that you can have a mix of all, but if you remove the "bad/bad" restaurant there is a correlation that appears, but it is due to the collider bias.
- TeMPOraL 2y ago
  > if you remove the "bad/bad" restaurant there is a correlation that appears, but it is due to the collider bias. This sounds like the correlation appears because of you throwing away some data, but the way I see it, that correlation is real - you're not removing the bad/bad restaurants, the market is. I've been reading up on collider bias on Wiki and pondering the examples[0] - restaurants, dating, celebrities - and the way I see it, the biased statistics is still true for whoever is doing the classification (person visiting fast-food restaurants, or looking for a date), and if their selection (taste) generalizes, it might also carry over to the general population. I feel the restaurant example from Wiki, with its associated image below, is worth discussing: https://en.wikipedia.org/wiki/Berkson%27s_paradox#/media/File:Berkson.png https://en.wikipedia.org/wiki/Berkson%27s_paradox#/media/Fil... "An illustration of Berkson's Paradox. The top graph represents the actual distribution, in which a positive correlation between quality of burgers and fries is observed. However, an individual who does not eat at any location where both are bad observes only the distribution on the bottom graph, which appears to show a negative correlation." This feels wrong to me. Why is the regression line nearly horizontal when, eyeballing the graph, a nearly vertical one would fit better and capture an even stronger positive correlation between qualities of hamburgers and fries? In fact, I'm tempted to even throw away the leftmost and rightmost points on the lower panel as outliers. Anyway, this example assumes the bad/bad restaurants are not visited by the subject - however, if we take your scenario where bad/bad restaurants quickly go out of business, then it's the market that creates the correlation between those two hypothetically independent qualities, so as long as we're talking real world and not some imaginary spherical restaurants in frictionless vacuum, it would be fair to say the correlation exists (and that the causal mechanism behind it is market selection). -- [0] - https://en.wikipedia.org/wiki/Berkson%27s_paradox https://en.wikipedia.org/wiki/Berkson%27s_paradox
drpixie 2y ago
Paris is a special case - you've got a great metro and everywhere is close to a station :) Perhaps distance to a non-metro station (eg a TER "mainline" station like Gare du Nord) would give more representative results? I wait with interest.
larodi 2y ago
I’d love to see more spatial sql applied. As a side effect tbh your code may get shorter. Even though R and Python are type go-to langs for ML, it is SQL which excels at spatial analysis.
isoprophlex 2y ago
I just want to tell you that it's very well written, well done! > With a mighty Pearson's correlation of 0.091, the data indicates that this could be true! I almost choked on this bit, as I was eating a sandwich (not a kebab sadly)
3abiton 2y ago
> I suppose I need to start working on part 2.... I'll wait for the ignobel paper.

by JmsPae 2y ago

dr_kiszonka 2y ago

Try fitting something non-linear or simply plot a mean (or median) rating over distance with some smoothing.

wjholden 2y ago

Which R-Tree Rust library were you referring to?

JmsPae 2y ago
https://github.com/georust/rstar https://github.com/georust/rstar Banger library. Not sure how it compares to, say, kd-tree in terms of performance but it allows for plenty of primitives.

lqet 2y ago

Why did you include metro stations in your study? The original quote only included train stations. The metro originally largely replaced a tram network, so the metro station density in Paris is higher than for other underground systems. I think it is very hard to find kebap shops in Paris that are not within 500 m of a metro station. This kind of dilutes the significance of your study, because I never really noticed that metro stations had a negative impact on their surrounding area (the opposite, really). I think your study would have been much more interesting (but not that algorithmically challenging...) if you only included the large train stations in Paris.

maeln 2y ago
I would second this. In Paris, but I find it to be true in most European city, the area surrounding train station is usually not very nice. It is usually surrounded by cheap hotel for 1-night traveler, overpriced fast food (hence the initial theory) and social housing / cheap building (a lot of people don't want to live next to a train station due to the nuisance, so poor people often get stuck there). On the other hand, metro station are pretty much anywhere, and they tend to have the opposite effect. Having a metro station close by is very practical and doesn't generate as much nuisance since it is underground and pretty well hidden. I am almost sure the data will look very different if you only look for train station.
- yard2010 2y ago
  This is such a dystopian phenomenon, I'm far from an expert but I guess it's a matter of city planning?
  - lqet 2y ago
    It's very hard to avoid this. It's mostly a combination of railway noise, throughput of a large number of people who are only travelling through, opportunities for pickpockets and beggars, and historically of soot and air pollution by steam engines, which makes these areas unattractive to live in. And it is not for lack of trying. City planners since at least the 1850ies have been trying to improve the areas surrounding large train stations.
    - Symbiote 2y ago
      It's also a very large building or roofed space, where it's more difficult than elsewhere to accuse homeless etc of loitering.
  - Beretta_Vexee 2y ago
    It is difficult to avoid, as metro passengers are mainly residents or workers in nearby premises. Station halls are also much bigger and attract the marginalised who want to shelter from the elements.

randomcarbloke 2y ago

please do berlin, london, and stockholm.

vanderZwan 2y ago
Yeah, this is a nice selection of European cities to compare! Having lived in Berlin and Stockholm (and a few other cities), I'd say Stockholm has by far the worst kebab options of all places I've lived, while Berlin was the best one. I'm curious whether this is reflected in local reviews, or whether the locals just lower or heighten their standards based on the what the average food quality is like.
- vidarh 2y ago
  Kebabs are one of the foods (like Chinese cuisine) that morphs depending on a combination of which kebab-eating group brought it to the country, and local cuisine. I'm not sure about Stockholm, or Sweden in general, when it comes to kebabs, but kebabs in Norway bear little resemblance to the kebabs I get in London. And the UK now has a chain serving "German" kebabs, which again are significantly different from the kebabs we get from Turkish takeaway places and restaurants here... It's not that they're better or worse - I might crave one or the other depending on what I'm in the mood for, as they're almost different dishes. So, comparing cities against each other is a lot harder than comparing differences in local opinion by location within a city.
  - phist_mcgee 2y ago
    Kebabs in Australia are basically a different food to the one you get in continental Europe. Good, but different.
  - randomcarbloke 2y ago
    The author is Swedish, and having asked some Swedes they basically consider the kebab to be the goto "local" cuisine. London of course has the two styles, |Turkish| and Turkish via Germany.
- ido 2y ago

percevalve 2y ago

That looks like a typical collider bias to me... There should be no correlation between location and quality... But as you are looking at restaurant that are still "in business" you are introducing a bias. If you simplify, a restaurant can have : - good/bad location - good/bad food If your restaurant has bad location and bad food, it is not going to stay in business very long. After that you can have a mix of all, but if you remove the "bad/bad" restaurant there is a correlation that appears, but it is due to the collider bias.

TeMPOraL 2y ago
> if you remove the "bad/bad" restaurant there is a correlation that appears, but it is due to the collider bias. This sounds like the correlation appears because of you throwing away some data, but the way I see it, that correlation is real - you're not removing the bad/bad restaurants, the market is. I've been reading up on collider bias on Wiki and pondering the examples[0] - restaurants, dating, celebrities - and the way I see it, the biased statistics is still true for whoever is doing the classification (person visiting fast-food restaurants, or looking for a date), and if their selection (taste) generalizes, it might also carry over to the general population. I feel the restaurant example from Wiki, with its associated image below, is worth discussing: https://en.wikipedia.org/wiki/Berkson%27s_paradox#/media/File:Berkson.png https://en.wikipedia.org/wiki/Berkson%27s_paradox#/media/Fil... "An illustration of Berkson's Paradox. The top graph represents the actual distribution, in which a positive correlation between quality of burgers and fries is observed. However, an individual who does not eat at any location where both are bad observes only the distribution on the bottom graph, which appears to show a negative correlation." This feels wrong to me. Why is the regression line nearly horizontal when, eyeballing the graph, a nearly vertical one would fit better and capture an even stronger positive correlation between qualities of hamburgers and fries? In fact, I'm tempted to even throw away the leftmost and rightmost points on the lower panel as outliers. Anyway, this example assumes the bad/bad restaurants are not visited by the subject - however, if we take your scenario where bad/bad restaurants quickly go out of business, then it's the market that creates the correlation between those two hypothetically independent qualities, so as long as we're talking real world and not some imaginary spherical restaurants in frictionless vacuum, it would be fair to say the correlation exists (and that the causal mechanism behind it is market selection). -- [0] - https://en.wikipedia.org/wiki/Berkson%27s_paradox https://en.wikipedia.org/wiki/Berkson%27s_paradox

drpixie 2y ago

Paris is a special case - you've got a great metro and everywhere is close to a station :) Perhaps distance to a non-metro station (eg a TER "mainline" station like Gare du Nord) would give more representative results? I wait with interest.

larodi 2y ago

I’d love to see more spatial sql applied. As a side effect tbh your code may get shorter. Even though R and Python are type go-to langs for ML, it is SQL which excels at spatial analysis.

isoprophlex 2y ago

I just want to tell you that it's very well written, well done! > With a mighty Pearson's correlation of 0.091, the data indicates that this could be true! I almost choked on this bit, as I was eating a sandwich (not a kebab sadly)

3abiton 2y ago

> I suppose I need to start working on part 2.... I'll wait for the ignobel paper.