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0 pointslogfromblammo8y ago0 comments

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.

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BugsJustFindMe8y ago

What you're saying doesn't match the reality of what is actually shown in the graph at 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.

yuliyp8y ago

Births and deaths are derivatives. Thus a 25% spike is basically just an adjustment to reflect smaller (~2-3%) errors in the non-census years. To put numbers to this: imagine 100 people were born every year between 1991 and 2000, inclusive. The statistics only recorded 98 people being born every year, though. We then did a census, and discovered that the number of people <10 years old in 2000 was 1000 people, thus we recorded a number of births as 118 (since we thought that 882 people had been born so far in 1991-1999), and then back down to 100 in the next year.

logfromblammoOP8y 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).

BugsJustFindMe8y 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.

EamonnMR8y ago

If anyone would like to know more about the 1890 census (I was intrigued) this is a good article on it:

https://www.archives.gov/publications/prologue/1996/spring/1...

j / k navigate · click thread line to collapse

0 comments

BugsJustFindMe8y ago

What you're saying doesn't match the reality of what is actually shown in the graph at http://usafacts.org/metrics/12966

yuliyp8y ago

logfromblammoOP8y 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).

BugsJustFindMe8y 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.

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.

EamonnMR8y ago

If anyone would like to know more about the 1890 census (I was intrigued) this is a good article on it:

https://www.archives.gov/publications/prologue/1996/spring/1...

j / k navigate · click thread line to collapse