5 ms·

Isn't this just likely to be caused by the census data?

BugsJustFindMe 10y ago
You mean people are more likely to die in census years? I mean, it could be true, but I'm not willing to bet on it. [edit] So I went and put "why is death rate higher in census years?" into the google search bar, and the first result is "Causes of Death - Census". I didn't actually click on the link to find out, but that title certainly sounds like the census kills people. So maybe you're right. :)
- deleted 10y ago
  [deleted]
- odonnellryan 10y ago
  I think it's just that the intermediary years are estimations and the chart isn't compensated. The estimates are just bad and not adjusted historically. Doesn't make the chart bad... just makes the data a little wonky.
  - BugsJustFindMe 10y ago
    It sounds like you're inventing reasons to post-hoc rationalize bad data. What exactly are the intermediate years estimates of? What does "isn't compensated" even mean in this context? Doesn't make the chart bad... just makes the data a little wonky. The chart is great. It perfectly represents exactly the data in the tabular form. The data is apparently garbage though.
  - dragonwriter 10y ago
    The intermediate years use statistical methods that better address some of the practical difficulties in getting complete and unique responses; the "actual enumeration" is well-known to be less accurate (in fact, the same methods used for between census estimates are also used by the census bureau to produce and publish estimates of the over- and under-counts in the actual enumeration.) There was (probably still is, despite the fact that it seems to be a lost cause) a movement to use the better methods for all purposes, but given that it would be a constitutional change and the errors benefit the already politically powerful, there is pretty much no chance of it happening any time in the foreseeable future. OTOH, I don't know ow that that actually has anything to do with the chart at issue: there is no information on sources or methodology, just "sources of this data are coming soon". If you don't have the sources ready to cite, you have no business publishing visualizations of the supposed data.
logfromblammo 10y ago
Or more precisely, by the lack of census data in years where no actual enumeration is performed. The big jumps on census years indicate that the census department does not estimate accurately when working with 9-year-old data.
- BugsJustFindMe 10y ago
  What you're saying doesn't match the reality of what is actually shown in the graph at http://usafacts.org/metrics/12966 http://usafacts.org/metrics/12966 They aren't jumps suddenly correcting a bad estimate with new data. They are gigantic 25% spikes which are then immediately undone. There is no way to explain this chart by just saying that estimates worsen over time.
  - logfromblammo 10y ago
    Depending on the estimate, the most recent census data might not be fully incorporated into the model until several years following the census? I can't look at your link at the moment because the corporate firewall is currently blocking the domain. But there really isn't any way to get around the fact that real census data are only collected once every 10 years (and the 1890 census was burned, so that point is missing).
    - BugsJustFindMe 10y ago
      When you can look at the links you'll see what I mean. To give a description of the problem in text... Both charts are labeled "Deaths", but I'm going to describe one of them for you. The time span from 1981 to 1999 goes like this: 1,968,365 - 1,998,559 - 2,033,124 - 2,068,679 - 2,091,359 - 2,105,024 - 2,163,984 - 2,161,764 - [1,637,394] - [2,656,721] - 2,180,115 - 2,226,027 - 2,282,854 - 2,284,363 - 2,317,918 - 2,321,933 - 2,330,759 - 2,359,088 - 2,386,995 And then 2000 is [2,979,442] And then 2001 is 2,430,225 And so on. Every 10 years, and also in 1989, there is a fluctuation by 500,000 deaths from the expected number given the surrounding trends. All of the numbers that are _not_ between [] above look like a smooth upward trend, yeah? So WTF is happening in the three that have [] if the data isn't bogus? I say the data must be bogus.

You mean people are more likely to die in census years? I mean, it could be true, but I'm not willing to bet on it. [edit] So I went and put "why is death rate higher in census years?" into the google search bar, and the first result is "Causes of Death - Census". I didn't actually click on the link to find out, but that title certainly sounds like the census kills people. So maybe you're right. :)

deleted 10y ago
[deleted]
odonnellryan 10y ago
I think it's just that the intermediary years are estimations and the chart isn't compensated. The estimates are just bad and not adjusted historically. Doesn't make the chart bad... just makes the data a little wonky.
- BugsJustFindMe 10y ago
  It sounds like you're inventing reasons to post-hoc rationalize bad data. What exactly are the intermediate years estimates of? What does "isn't compensated" even mean in this context? Doesn't make the chart bad... just makes the data a little wonky. The chart is great. It perfectly represents exactly the data in the tabular form. The data is apparently garbage though.
- dragonwriter 10y ago
  The intermediate years use statistical methods that better address some of the practical difficulties in getting complete and unique responses; the "actual enumeration" is well-known to be less accurate (in fact, the same methods used for between census estimates are also used by the census bureau to produce and publish estimates of the over- and under-counts in the actual enumeration.) There was (probably still is, despite the fact that it seems to be a lost cause) a movement to use the better methods for all purposes, but given that it would be a constitutional change and the errors benefit the already politically powerful, there is pretty much no chance of it happening any time in the foreseeable future. OTOH, I don't know ow that that actually has anything to do with the chart at issue: there is no information on sources or methodology, just "sources of this data are coming soon". If you don't have the sources ready to cite, you have no business publishing visualizations of the supposed data.

logfromblammo 10y ago

Or more precisely, by the lack of census data in years where no actual enumeration is performed. The big jumps on census years indicate that the census department does not estimate accurately when working with 9-year-old data.

BugsJustFindMe 10y ago
What you're saying doesn't match the reality of what is actually shown in the graph at http://usafacts.org/metrics/12966 http://usafacts.org/metrics/12966 They aren't jumps suddenly correcting a bad estimate with new data. They are gigantic 25% spikes which are then immediately undone. There is no way to explain this chart by just saying that estimates worsen over time.
- logfromblammo 10y ago
  Depending on the estimate, the most recent census data might not be fully incorporated into the model until several years following the census? I can't look at your link at the moment because the corporate firewall is currently blocking the domain. But there really isn't any way to get around the fact that real census data are only collected once every 10 years (and the 1890 census was burned, so that point is missing).
  - BugsJustFindMe 10y ago
    When you can look at the links you'll see what I mean. To give a description of the problem in text... Both charts are labeled "Deaths", but I'm going to describe one of them for you. The time span from 1981 to 1999 goes like this: 1,968,365 - 1,998,559 - 2,033,124 - 2,068,679 - 2,091,359 - 2,105,024 - 2,163,984 - 2,161,764 - [1,637,394] - [2,656,721] - 2,180,115 - 2,226,027 - 2,282,854 - 2,284,363 - 2,317,918 - 2,321,933 - 2,330,759 - 2,359,088 - 2,386,995 And then 2000 is [2,979,442] And then 2001 is 2,430,225 And so on. Every 10 years, and also in 1989, there is a fluctuation by 500,000 deaths from the expected number given the surrounding trends. All of the numbers that are _not_ between [] above look like a smooth upward trend, yeah? So WTF is happening in the three that have [] if the data isn't bogus? I say the data must be bogus.