5 ms·

It's not clear what technical content this post has. A cubic polynomial vs time would be a terrible idea, but the dashed and/or dotted red line (that people see

It's not clear what technical content this post has. A cubic polynomial vs time would be a terrible idea, but the dashed and/or dotted red line (that people seem upset about) is obviously not a cubic polynomial vs time. At that point I run out of guesses about exactly what's being said by anybody.

kbenson 6y ago
I think there's actually two things going on here. There's what this post is talking about, which is a general lack of understanding of statistics, which is likely true and correct, and likely for both reasons that are explored here. Then there's the reason to actually even talk about this specific instance, which is that there is a complete lack of operating on the assumption of good faith and clarifying intent before making assertions as to other peoples intentions which is rampant currently. Whether it's rampant on twitter and between political parties or has spilled into other areas such that it's harder to have coherent discussions in general now than it was in years past I'm not sure. There are a lot of assumptions in that reply to the tweet in question that's shown. It's not even a novel set of assumptions, it's the standard twitter fare of "I assume he means X and this thing doesn't explicitly show X therefore he must not understand what he's talking about." Any nuance such as using a secondary aspect of something to outline a potion of what you mean is immediately ignored, and if pointed out later assumed to be covering up after the fact.
- AnimalMuppet 6y ago
  Well, if you want to express nuance, Twitter might not be the medium for you...
  - kbenson 6y ago
    Lol, I believe that. The problem is that these days it seems like the message either has to be only visible by friendlies, or reduced to the simplest and rote version that's impossible to misinterpret if you want to avoid people trying to tear it apart, and even then they'll sometimes pull it into some wider framework of society and what it means when views through the lens of X, Y and Z and why you should be mad. That's a high bar to hit just to tweet something. It's crazy, and twitter's where it's easiest to see, but you can also use a news aggregator like news.google.com and get a good dose of it just from the headlines about what is ostensibly the same story from different news agencies. Wild times.
- unishark 6y ago
  > ...there is a complete lack of operating on the assumption of good faith and clarifying intent before making assertions as to other peoples intentions which is rampant currently. This is basically what all politics is. People projecting thoughts (or lack thereof) in bad faith on each other. Though it does seem that the fraction of society sucked into this toxic discourse has grown to cover practically everything lately (in the US anyway). But also the outrage machine of Twitter etc is obviously biased toward the extreme views and outliers. Where 99/100 people might say 'meh, another failure to predict the future like most', the remaining 1/100 blows his top and gets the attention.
  - friendlybus 6y ago
    For all the negativity out there, there is a lot more clarity in challenging bad interpretations. I havent learnt as much online recently as I have in 15 yrs on the net.
smnthermes 6y ago
The article may not have technical content, but the title certainly is true: http://pseudoexpertise.com/ http://pseudoexpertise.com/
- thedudeabides5 6y ago
  Well the flame is saying it's a misunderstanding of the difference between data smoothing and model-based forecasting. To which I'd say that just begs the question of if there's a difference to begin with, and what criteria you would use to distinguish them if they are.
  - mcnamaratw 6y ago
    Of course there's a difference between smoothing and forecasting. It's the difference between interpolation and extrapolation. But I can't figure out what anyone in the original discussion is really saying, if anything.
  - dunkelheit 6y ago
    To begin, if the curve doesn't extend into the future, it can't forecast anything.
Animats 6y ago
Um, yes. The statistical community has not been doing well with the coronavirus epidemic. Nobody's models seem to be predicting well. Nor is the source data for anything but deaths very good. This matters, because the current plan US plan seems to be "open things up and wait for herd immunity". How much time, and how many deaths, lie between now and that point? I dunno.
- bradford 6y ago
  > The statistical community has not been doing well with the coronavirus epidemic. I'm curious how you concluded this. Can you (or anyone) recommend a reasoned evaluation of the existing models? We've got a few months of hindsight now and I'm curious hear what any reputable data scientist might have to say. I see criticism of the models online (in op-eds and social media), but the criticisms are usually agenda driven and opaque on technical details, which isn't particularly helpful.
  - Animats 6y ago
    The actuals from now and the predictions from a few weeks ago aren't aligning quantitatively. The shapes of the curves, though, do make sense. Here's the Financial Times graph of actuals, country by country.[1] No predictions. The pattern that shows up in some of the actuals is "huge spike, tight lockdown, big drop". See Italy, Belgium and the Isle of Man. The Isle of Man puts people in jail for weeks for violating quarantine rules. The US didn't have a huge spike, but isn't seeing a big drop, either. US deaths are at about 2/3 of peak. [1] https://ig.ft.com/coronavirus-chart/?areas=usa&areas=gbr&areasRegional=usny&areasRegional=usnj&cumulative=0&logScale=0&perMillion=1&values=deaths https://ig.ft.com/coronavirus-chart/?areas=usa&areas=gbr&are...
- cco 6y ago
  > This matters, because the current plan US plan seems to be "open things up and wait for herd immunity". How much time, and how many deaths, lie between now and that point? I dunno. This seems pretty straightforward, no? You re-open cautiously, wait a few weeks, make sure your hospital resources aren't being overwhelmed, then open up a bit more, rinse and repeat. I wasn't aware there was another way.
dunkelheit 6y ago
> It's not clear what technical content this post has. Indeed. The post is a big exercise in strawmanning (and of course ad hominem but I am willing to forgive it because it adds entertainment value). Andrew Gelman (a well-known statistics expert) dunks on some guy because he dared to defend a shitty graphic and "made a statistical error". Which is kind of unfair, because he didn't do any statistics. Of course when our brains see some curves they can't resist the temptation to do some statistics on their own, but bad dataviz is a different sin than bad statistics and should be treated as such.
starpilot 6y ago
> A cubic polynomial vs time would be a terrible idea, but the dashed and/or dotted red line (that people seem upset about) is obviously not a cubic polynomial vs time. What? The chart's creator said it was a cubic polynomial. Mr. Hassett said he had employed ‘just a canned function in Excel, a cubic polynomial.’” https://www.vox.com/2020/5/8/21250641/kevin-hassett-cubic-model-smoothing https://www.vox.com/2020/5/8/21250641/kevin-hassett-cubic-mo...
- dnautics 6y ago
  on the other hand, for reals calculus (namely taylor polynomial estimation) also says, "why not a cubic polynomial?"
  - CrazyStat 6y ago
    Because Taylor approximations can lose accuracy very quickly as you move away from the point they are centered around. There are available epidemiological models that are actually grounded in a scientific understanding of the problem. "Why not a cubic polynomial?" is a stupid question.
    - mcnamaratw 6y ago
      "Why not a cubic polynomial?" taken literally is not a stupid question at all. No, it's not a contribution to understanding the problem at the professional level, but it is a fundamental and important question. Somebody persists after hearing the answer (which you gave), that might be stupid.
    - dnautics 6y ago
      Yes, and until you do the correct analysis and estimate just how bad the estimate is going to be (off by 10%? Off by 50%? An order of magnitude?) You can't just dismiss it out of hand. So how far off will it be?
      - CrazyStat 6y ago
        The cubic is going to go to either +infinity or -infinity, so it will eventually be of by infinity%. Or infinity orders of magnitude. I feel like I can dismiss it now.
adfsdfs 6y ago
I think it resembles a cubic spline kernel, FWIW.
- mcnamaratw 6y ago
  Yeah that could be it. But in that case what's the big deal? The data is a messy bump on a log, the fit is a smooth bump on a log. That kind of fit is useless for prediction, but they say so explicitly.

kbenson 6y ago

I think there's actually two things going on here. There's what this post is talking about, which is a general lack of understanding of statistics, which is likely true and correct, and likely for both reasons that are explored here. Then there's the reason to actually even talk about this specific instance, which is that there is a complete lack of operating on the assumption of good faith and clarifying intent before making assertions as to other peoples intentions which is rampant currently. Whether it's rampant on twitter and between political parties or has spilled into other areas such that it's harder to have coherent discussions in general now than it was in years past I'm not sure. There are a lot of assumptions in that reply to the tweet in question that's shown. It's not even a novel set of assumptions, it's the standard twitter fare of "I assume he means X and this thing doesn't explicitly show X therefore he must not understand what he's talking about." Any nuance such as using a secondary aspect of something to outline a potion of what you mean is immediately ignored, and if pointed out later assumed to be covering up after the fact.

AnimalMuppet 6y ago
Well, if you want to express nuance, Twitter might not be the medium for you...
- kbenson 6y ago
  Lol, I believe that. The problem is that these days it seems like the message either has to be only visible by friendlies, or reduced to the simplest and rote version that's impossible to misinterpret if you want to avoid people trying to tear it apart, and even then they'll sometimes pull it into some wider framework of society and what it means when views through the lens of X, Y and Z and why you should be mad. That's a high bar to hit just to tweet something. It's crazy, and twitter's where it's easiest to see, but you can also use a news aggregator like news.google.com and get a good dose of it just from the headlines about what is ostensibly the same story from different news agencies. Wild times.
unishark 6y ago
> ...there is a complete lack of operating on the assumption of good faith and clarifying intent before making assertions as to other peoples intentions which is rampant currently. This is basically what all politics is. People projecting thoughts (or lack thereof) in bad faith on each other. Though it does seem that the fraction of society sucked into this toxic discourse has grown to cover practically everything lately (in the US anyway). But also the outrage machine of Twitter etc is obviously biased toward the extreme views and outliers. Where 99/100 people might say 'meh, another failure to predict the future like most', the remaining 1/100 blows his top and gets the attention.
- friendlybus 6y ago
  For all the negativity out there, there is a lot more clarity in challenging bad interpretations. I havent learnt as much online recently as I have in 15 yrs on the net.

smnthermes 6y ago

The article may not have technical content, but the title certainly is true: http://pseudoexpertise.com/ http://pseudoexpertise.com/

thedudeabides5 6y ago
Well the flame is saying it's a misunderstanding of the difference between data smoothing and model-based forecasting. To which I'd say that just begs the question of if there's a difference to begin with, and what criteria you would use to distinguish them if they are.
- mcnamaratw 6y ago
  Of course there's a difference between smoothing and forecasting. It's the difference between interpolation and extrapolation. But I can't figure out what anyone in the original discussion is really saying, if anything.
- dunkelheit 6y ago
  To begin, if the curve doesn't extend into the future, it can't forecast anything.

Animats 6y ago

Um, yes. The statistical community has not been doing well with the coronavirus epidemic. Nobody's models seem to be predicting well. Nor is the source data for anything but deaths very good. This matters, because the current plan US plan seems to be "open things up and wait for herd immunity". How much time, and how many deaths, lie between now and that point? I dunno.

bradford 6y ago
> The statistical community has not been doing well with the coronavirus epidemic. I'm curious how you concluded this. Can you (or anyone) recommend a reasoned evaluation of the existing models? We've got a few months of hindsight now and I'm curious hear what any reputable data scientist might have to say. I see criticism of the models online (in op-eds and social media), but the criticisms are usually agenda driven and opaque on technical details, which isn't particularly helpful.
- Animats 6y ago
  The actuals from now and the predictions from a few weeks ago aren't aligning quantitatively. The shapes of the curves, though, do make sense. Here's the Financial Times graph of actuals, country by country.[1] No predictions. The pattern that shows up in some of the actuals is "huge spike, tight lockdown, big drop". See Italy, Belgium and the Isle of Man. The Isle of Man puts people in jail for weeks for violating quarantine rules. The US didn't have a huge spike, but isn't seeing a big drop, either. US deaths are at about 2/3 of peak. [1] https://ig.ft.com/coronavirus-chart/?areas=usa&areas=gbr&areasRegional=usny&areasRegional=usnj&cumulative=0&logScale=0&perMillion=1&values=deaths https://ig.ft.com/coronavirus-chart/?areas=usa&areas=gbr&are...
cco 6y ago
> This matters, because the current plan US plan seems to be "open things up and wait for herd immunity". How much time, and how many deaths, lie between now and that point? I dunno. This seems pretty straightforward, no? You re-open cautiously, wait a few weeks, make sure your hospital resources aren't being overwhelmed, then open up a bit more, rinse and repeat. I wasn't aware there was another way.

dunkelheit 6y ago

> It's not clear what technical content this post has. Indeed. The post is a big exercise in strawmanning (and of course ad hominem but I am willing to forgive it because it adds entertainment value). Andrew Gelman (a well-known statistics expert) dunks on some guy because he dared to defend a shitty graphic and "made a statistical error". Which is kind of unfair, because he didn't do any statistics. Of course when our brains see some curves they can't resist the temptation to do some statistics on their own, but bad dataviz is a different sin than bad statistics and should be treated as such.

starpilot 6y ago

> A cubic polynomial vs time would be a terrible idea, but the dashed and/or dotted red line (that people seem upset about) is obviously not a cubic polynomial vs time. What? The chart's creator said it was a cubic polynomial. Mr. Hassett said he had employed ‘just a canned function in Excel, a cubic polynomial.’” https://www.vox.com/2020/5/8/21250641/kevin-hassett-cubic-model-smoothing https://www.vox.com/2020/5/8/21250641/kevin-hassett-cubic-mo...

dnautics 6y ago
on the other hand, for reals calculus (namely taylor polynomial estimation) also says, "why not a cubic polynomial?"
- CrazyStat 6y ago
  Because Taylor approximations can lose accuracy very quickly as you move away from the point they are centered around. There are available epidemiological models that are actually grounded in a scientific understanding of the problem. "Why not a cubic polynomial?" is a stupid question.
  - mcnamaratw 6y ago
    "Why not a cubic polynomial?" taken literally is not a stupid question at all. No, it's not a contribution to understanding the problem at the professional level, but it is a fundamental and important question. Somebody persists after hearing the answer (which you gave), that might be stupid.
  - dnautics 6y ago
    Yes, and until you do the correct analysis and estimate just how bad the estimate is going to be (off by 10%? Off by 50%? An order of magnitude?) You can't just dismiss it out of hand. So how far off will it be?
    - CrazyStat 6y ago
      The cubic is going to go to either +infinity or -infinity, so it will eventually be of by infinity%. Or infinity orders of magnitude. I feel like I can dismiss it now.

adfsdfs 6y ago

I think it resembles a cubic spline kernel, FWIW.

mcnamaratw 6y ago
Yeah that could be it. But in that case what's the big deal? The data is a messy bump on a log, the fit is a smooth bump on a log. That kind of fit is useless for prediction, but they say so explicitly.