5 ms·

You could say the opposite is true as well. How do you know after hours workers are not rating their productivity higher than actual? How do you know that the 9

You could say the opposite is true as well. How do you know after hours workers are not rating their productivity higher than actual? How do you know that the 9-5 workers aren’t rating their productivity as lower than usual? All data in of itself is useless. A sample pool of 10,000 volunteers is pretty good in the realm of statistics.

mym1990 3y ago
“All data in of itself is useless”…what does that even mean? That’s like saying a chair in of itself is useless because no one is sitting in it. And this could be extrapolated to saying everything is useless. Data’s usefulness stems first from its many defining factors, which validates it, and then opens doors to using that data to explore insights.
- deleted 3y ago
  [deleted]
- richk449 3y ago
  > And this could be extrapolated to saying everything is useless. Now we are getting somewhere.
  - mym1990 3y ago
    I mean I can do mental gymnastics to understand the sentiment, but it really just comes down to individual preferences and definition of "use". To me, the usefulness of everything is in constant flux, and that's kind of cool to think about.
    - richk449 3y ago
      I thought your comment was spot on. I just appreciated the possible turn towards nihilism or existentialism. We spend so much of our life determining what is useful in one sense of the word, and rarely stop to think about the usefulness of what we do in the philosophical sense.
halfcat 3y ago
It’s the nature of the study that parent comment is referring to. If a study is self-reporting, it’s an observational study which can only establish correlation, meaning the study can only say, “there might be something here that warrants a further research”. A clinical trial is needed to establish causation. So while 10k sample size reduces the error bars, it only increases the confidence that there might be something here worth doing a more rigorous study later.
kortilla 3y ago
> A sample pool of 10,000 volunteers is pretty good in the realm of statistics. No it’s not. No sample size can make up for other biases.
robertlagrant 3y ago
> All data in of itself is useless. A sample pool of 10,000 volunteers is pretty good in the realm of statistics. The point isn't the size. The point is there are too many confounding factors. It could be that people who work longer hours do so because they are high on trait conscientiousness, which also causes them to report low productivity It could even be because they are conscientious that they actually work slightly slower, and/or it could be that people who are less conscientious just don't care as mcuh about producing what was expected. To paraphrase the late Hitch: productivity metrics are not great. Neither is the word "connection" in science-adjacent reporting.

mym1990 3y ago

“All data in of itself is useless”…what does that even mean? That’s like saying a chair in of itself is useless because no one is sitting in it. And this could be extrapolated to saying everything is useless. Data’s usefulness stems first from its many defining factors, which validates it, and then opens doors to using that data to explore insights.

deleted 3y ago
[deleted]
richk449 3y ago
> And this could be extrapolated to saying everything is useless. Now we are getting somewhere.
- mym1990 3y ago
  I mean I can do mental gymnastics to understand the sentiment, but it really just comes down to individual preferences and definition of "use". To me, the usefulness of everything is in constant flux, and that's kind of cool to think about.
  - richk449 3y ago
    I thought your comment was spot on. I just appreciated the possible turn towards nihilism or existentialism. We spend so much of our life determining what is useful in one sense of the word, and rarely stop to think about the usefulness of what we do in the philosophical sense.

halfcat 3y ago

It’s the nature of the study that parent comment is referring to. If a study is self-reporting, it’s an observational study which can only establish correlation, meaning the study can only say, “there might be something here that warrants a further research”. A clinical trial is needed to establish causation. So while 10k sample size reduces the error bars, it only increases the confidence that there might be something here worth doing a more rigorous study later.

kortilla 3y ago

> A sample pool of 10,000 volunteers is pretty good in the realm of statistics. No it’s not. No sample size can make up for other biases.

robertlagrant 3y ago

> All data in of itself is useless. A sample pool of 10,000 volunteers is pretty good in the realm of statistics. The point isn't the size. The point is there are too many confounding factors. It could be that people who work longer hours do so because they are high on trait conscientiousness, which also causes them to report low productivity It could even be because they are conscientious that they actually work slightly slower, and/or it could be that people who are less conscientious just don't care as mcuh about producing what was expected. To paraphrase the late Hitch: productivity metrics are not great. Neither is the word "connection" in science-adjacent reporting.