You, Yes You, Are To Blame For Junk Stats
from the 9-out-of-10-people-disagree dept
It's pretty easy to find examples of bad statistics, whether they stem from poor data collection or interpretation. But a writer over at the BBC thinks he's fingered the real culprit: people who respond to surveys incorrectly. While on one level, his claim may have a little bit of truth to it, it really seems like an abdication of responsibility for the media, who all too often don't check out the bogus stats they cite, or swallow manipulated data without much question. Furthermore, when many groups use push polls not just to collect data, but to influence opinions, it's hard to blame the average respondent too much. In short, bad responses to survey questions could be a problem -- but that doesn't excuse the people collecting the data, and especially the media reporting it, from ignoring the issue. If they know the data's inaccurate, why do they keep reporting it?![Hide This Hide this](https://ii.techdirt.com/s/t/i/topclose.png)
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Filed Under: junk stats, stats
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examples of Bad
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The obvious outcome of all this?...Media should stop concocting and reporting these stats as if they actually mean something.
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Amazing spam
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Just use another poll to analyse the first one
Enough said.
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http://latimesblogs.latimes.com/technology/2009/06/bittorrent-vuze-survey-purchasing-dvd.h tml
I think that is the best example of junk stats possible. Their survey group including almost 65% Vuse users, in a study published by, well, Vuse. Talk about misleading and meaningless junk stats. Yet Carlo, your boss ran with this story like it had come from on high, because it supports his (still unproven) concept that somehow people who download everything are still willing to pay for it, and more often than people who don't.
Really, you should chat with Mike before you put these things up, because it would seem that the two of you just don't agree.
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Unemployment
From OECD normalized numbers for 2007 (latest available):
* men aged 25-54
employment divided by population
France: 88.3% (hence 11.7% jobless)
USA: 87.5% (hence 12.5% jobless)
normalized unemployment rate
France: 6.3%
USA: 3.7%
So with a slightly higher relative working population in this age/sex group France has ... a 70% higher unemployment rate than the USA.
* women aged 25-54
E/P
FR 76.1
USA 72.5
unemployment
FR 7.7
USA 3.8
So here we have clearly more women working in France (3.6 percentage point) relative to their population but unemployment is 102% higher in France!
* conclusion
Employment/population is an objective measure. Unemployment is an extremely subjective measure and so it's easy to get very wide discrepancies as shown above.
* question
Any paper studying this discrepancy in OECD normalized numbers? For male 25-54 there's no real reason not to work, so what are all those USA men doing?
* second question
What credit do you place on "empirical validation" of economic theories (and papers) who use unemployment by country to select the right policy?
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Surveys
There doesn't seem to be enough middle ground between some of the answers, and sometimes there isn't a viable answer avialable, or the question doesn't apply to me at all, based on previous answers I've given or my current situation.
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My fault
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Guilty as charged!
Thats me, giving out bad answers as usual.
If you ring me in the middle of my dinner (actually if you ring me at all and I haven't requested it) of course your going to get a skewed results.
If your web site insists on a pop-up for a survey and it keeps poping up then yes, your going to get cr*p answers.
If you keep sending me e-mail to fill out a survey then you only have yourself to blame.
And one guarenteed lost customer.
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