3 ms·

Sure, but you're not "supposed" to. Or maybe you are, which is the problem. "Inconclusive" or "negative" results are just as meaningful (i.e. no conclusion is

by throwaway1980 13y ago

Sure, but you're not "supposed" to. Or maybe you are, which is the problem. "Inconclusive" or "negative" results are just as meaningful (i.e. no conclusion is still a conclusion), but we're biased towards "positive" results showing identifiable correlations.

tks2103 13y ago
i dont understand what you are trying to say. data certainly do not have preconceived notions, but i dont think that is your point. people are not supposed to draw conclusions from data? that sounds like exactly what people are supposed to do, if they are to survive. is your point that humans are biased towards certain results? that does not follow from your earlier two points ("Data aren't supposed to..." and "Sure, but you're not 'supposed' to..."). why do you think humans are biased towards "positive" results?
- icambron 13y ago
  You're missing Throwaway's point entirely. The context from higher in the thread: > I'm not sure what they are supposed to show. In other words, "in the context of what argument are you presenting this data?" Throwaway is saying that the person presenting the data needn't have an intended conclusion; it doesn't need to be part of an argument at all. It's OK, in fact preferred, for it just to be data from which you can draw conclusions, or decide there are no interesting conclusions to draw.
  - Dylan16807 13y ago
    Except that they do need to have a conclusion. Otherwise they're wasting everyone's time showing off "this data is meaningless". The only time you want to show 'no pattern' is if someone asked for data for/against a pattern.
    - throwaway1980 13y ago
      There is no such thing as meaningless data. Data are just observations. Meaning is constructed from the interpretation of data. The primary questions of good science are what, where, when, and who. These are the questions you answer when you collect data. Once you've answered them you can address secondary questions of why and how. Asking why and how without giving priority to what, where, when, and who is putting the cart before the horse. When you are unable to answer why and how for a given set of data, it is not meaningless. Rather, the lack of correlation or explanations just says that perhaps we need to look into this more deeply. "I've looked at the data and I don't know" is a profound statement, and it can be inspiring. Science also has to be falsifiable, and effectively that's what these graphs do, at least as far as extrapolating from the NY study goes. I agree it would have been more helpful if the author had presented conclusions about what the data mean or don't mean, but they aren't a priori meaningless simply because there isn't a visible correlation. No correlation, which is the rather obvious conclusion, is just as meaningful. I hope this is more clear.
      - Dylan16807 13y ago
        Data that answers a question nobody wants answered is effectively meaningless. If you are showing a lack of correlation in a situation where a correlation might be expected then good job. If you are showing a lack of correlation between giraffe migration and cactus branch count then you're wasting everyone's time by bringing it up.
        throwaway1980 13y ago
        There are multiple questions here: What do the transit vs. income graphs for SF look like? How do the SF graphs compare to the NY ones? Is there a clustering of rich and poor stops in SF like there is in NY? And then finally, what are the possible explanations? Sure, they didn't answer the last question, and you have to inspect the data to answer the second and third ones, but it's okay to provide data for other people to look at. Surely if the first question was worth answering for NY, it's worth answering for SF. You don't answer questions simply because you expect to find something, you answer them because you're curious. Do you know the story about Richard Feynman and the wobbling plate in the cafeteria? It's another question that "nobody wanted to answer". https://www.youtube.com/watch?v=x98SEQUo48c https://www.youtube.com/watch?v=x98SEQUo48c
brazzy 13y ago
That's because there is no value in gathering and publishing data for its own sake. Conclusive results are valuable because you can act on them to achieve something. And there's nothing wrong with that. Ignoring inconclusive/negative data is only problematic if it contradicts the data you choose to act on.
- throwaway1980 13y ago
  What about genome sequencing? Or census taking? Or benchmark characterization? There is quite a bit of data publishing that is valuable to other researchers. Talking about what didn't work is good because it stops other people from repeating failed experiments. Finally, in this case, it does contradict the NY study.

tks2103 13y ago

i dont understand what you are trying to say. data certainly do not have preconceived notions, but i dont think that is your point. people are not supposed to draw conclusions from data? that sounds like exactly what people are supposed to do, if they are to survive. is your point that humans are biased towards certain results? that does not follow from your earlier two points ("Data aren't supposed to..." and "Sure, but you're not 'supposed' to..."). why do you think humans are biased towards "positive" results?

icambron 13y ago
You're missing Throwaway's point entirely. The context from higher in the thread: > I'm not sure what they are supposed to show. In other words, "in the context of what argument are you presenting this data?" Throwaway is saying that the person presenting the data needn't have an intended conclusion; it doesn't need to be part of an argument at all. It's OK, in fact preferred, for it just to be data from which you can draw conclusions, or decide there are no interesting conclusions to draw.
- Dylan16807 13y ago
  Except that they do need to have a conclusion. Otherwise they're wasting everyone's time showing off "this data is meaningless". The only time you want to show 'no pattern' is if someone asked for data for/against a pattern.
  - throwaway1980 13y ago
    There is no such thing as meaningless data. Data are just observations. Meaning is constructed from the interpretation of data. The primary questions of good science are what, where, when, and who. These are the questions you answer when you collect data. Once you've answered them you can address secondary questions of why and how. Asking why and how without giving priority to what, where, when, and who is putting the cart before the horse. When you are unable to answer why and how for a given set of data, it is not meaningless. Rather, the lack of correlation or explanations just says that perhaps we need to look into this more deeply. "I've looked at the data and I don't know" is a profound statement, and it can be inspiring. Science also has to be falsifiable, and effectively that's what these graphs do, at least as far as extrapolating from the NY study goes. I agree it would have been more helpful if the author had presented conclusions about what the data mean or don't mean, but they aren't a priori meaningless simply because there isn't a visible correlation. No correlation, which is the rather obvious conclusion, is just as meaningful. I hope this is more clear.
    - Dylan16807 13y ago
      Data that answers a question nobody wants answered is effectively meaningless. If you are showing a lack of correlation in a situation where a correlation might be expected then good job. If you are showing a lack of correlation between giraffe migration and cactus branch count then you're wasting everyone's time by bringing it up.
      - throwaway1980 13y ago
        There are multiple questions here: What do the transit vs. income graphs for SF look like? How do the SF graphs compare to the NY ones? Is there a clustering of rich and poor stops in SF like there is in NY? And then finally, what are the possible explanations? Sure, they didn't answer the last question, and you have to inspect the data to answer the second and third ones, but it's okay to provide data for other people to look at. Surely if the first question was worth answering for NY, it's worth answering for SF. You don't answer questions simply because you expect to find something, you answer them because you're curious. Do you know the story about Richard Feynman and the wobbling plate in the cafeteria? It's another question that "nobody wanted to answer". https://www.youtube.com/watch?v=x98SEQUo48c https://www.youtube.com/watch?v=x98SEQUo48c

brazzy 13y ago

That's because there is no value in gathering and publishing data for its own sake. Conclusive results are valuable because you can act on them to achieve something. And there's nothing wrong with that. Ignoring inconclusive/negative data is only problematic if it contradicts the data you choose to act on.

throwaway1980 13y ago
What about genome sequencing? Or census taking? Or benchmark characterization? There is quite a bit of data publishing that is valuable to other researchers. Talking about what didn't work is good because it stops other people from repeating failed experiments. Finally, in this case, it does contradict the NY study.