Re: With thanks to Tommy Cooper
Were his raspberry ripples on display?
9611 publicly visible posts • joined 11 Sep 2009
So they have to keep 100 yards apart? Mark out the distance using cones.
Anyway, it's good that they removed the sound from the chase video. I don't think I could have taken the mixing of "Greensleeves" and "Popeye The Sailor Man" at 30mph with all the Doppler effects and so on... that would definitely have pushed me over the edge.
You have a good point there. It definitely tells you something about the state of this nation. But what *other* criminal offence would there be?
I mean it's technically not a crime to have a secret blacklist of people is it? Well apart from the processing of data bit. It's what you do with it - like blacklisting people from the building trade for union activism etc. There are clubs that won't have you as a member if you're on a list... all now covered by GDPR. So that's the ONLY crime. I mean it's not morally right, but since when has immorality been automatically criminal? And there are other countries where this is much worse. Are there any nations better at this? Isn't it a reflection of the people?
That's a weird logical jump to make. They might be radicalised, say, and disposed to take action against the leaders of the religions of the kafirs, or the heads of state of countries that have supported the zionist oppressors or their allies, or the heads of state of a nation that mounted operations against righteous jihadists. King's has a rather well renowned Department of War Studies; probably one of the very few in existence.
Of course she should be forced. No-one sane would take on that job. It's the sort of role you have to be prepared for from birth. God bless her, she's done a great job for a whole lifetime, but would you actively choose that? That amount of being in the limelight has quite literally destroyed people before now.
Bloody hell. Did you bother to read the paper? Or anything? I just spent half a page explaining why you can't prove or even hint at causality with this kind of study. They never claimed any form of causality. The researchers are from NYU. The paper is only submitted, not accepted and hasn't been peer reviewed yet. It was presented at a conference. The funding hasn't been revealed (it should, and if I were reviewing it I would insist that section be included separately to the acknowledgments, as is common in Europe), there's no way to tell the colour of someone creating the tweets in their methodology, they do correct for racial make up of the areas, but that in itself could be a flaw.
You come along and try to explain the result with straw man examples, apparently just so you can string together a load of words you've seen lying around in the comments section of the Daily Mail. Honestly, I thought El Reg was better than that. Well, I guess they are, you can say generally what you like in the commentard sections. But equally if you're going to act like a tit there, expect to be called out for it.
I use the term "causal relationship" in the sense that it is used by just about everyone in science, engineering, etc
That being:
A causal relation between two events exists if the occurrence of the first causes the other.
The first event is called the cause and the second event is called the effect. Correlation between two events, variables or other measures does not imply causation. However the reverse is not true: if there is a causal relationship between two variables, they must ipso facto be correlated.
The very point of the example given was that as there is a correlation between drownings and ice cream sales, then the two events may both have causal relationships with a third event or variable. This same example set of data provided a whole year's worth of lectures, believe me! You start bringing in other data which may or may not be causally related, and you look for co-variance. This is all what these "AIs" like Watson do - look through massive data sets trying to identify co-variant relationships between stuff. You look at the dates on which these data were recorded. You plot them out on a timeline and see that both variables have some hint of a periodic cycle. The most obvious cycle is annual, so you look at "day of year" and find there's some correlation, some evidence of co-variance, but it's not staggeringly significant; it doesn't explain all the variance. You try it by month, and you get a much better figure. You try it by week of year and the correlation drops. You then correct for the day of the week by synthesising a value like first Saturday of Month n, second Friday of Month n. You then start lumping... Fridays in July, Saturdays in August...
This starts explaining the variance.
You then do something radical and expand your data set. You look at total visitor numbers, if such a figure exists. Damn, no-one was sat on the top of the Tower with a pair of binoculars counting people on the beach and people in the sea... so you take a proxy measure... the guy with the hand clicker at the piers turnstile. Woah! There's some kind of correlation there... But it doesn't explain everything still. So you look at the weather record, and you find there's a 99.999% explanation for ice cream sales linked to sunshine and high temperatures. But that only explains 87% of the drownings, but extreme BAD weather can explain another 12% of those.
So eventually you reach a point where you have all these correlations, and you are fairly certain that ice cream sales and drownings increase when the weather is fine and hot, when there are more people visiting the seaside, when it's a weekend, but that ice cream sales and drownings are negatively correlated when the weather is poor.
None of this actually gives any proof whatsoever for causality. It's reasonable to say that good weekend weather in the summer causes people to buy ice creams and to swim in the sea, and that swimming in the sea is the cause of some drownings. But there's still no proof. You'd have to conduct a controlled experiment to do that. You'd have to vary ice cream sales and monitor drownings in three different places or at three different times - one you leave as is, one you give away ice cream, the other you close the ice cream shop. You change one variable and see if the other changes.
Lo! Changing the amount of ice cream consumption on the coast does not affect the number of drownings. There is no causal relationship.
What experiment could you do to test the other correlations? I suppose you could ban swimming, close the beaches. Then visitor numbers could vary and the drownings wouldn't follow. Or force people into the sea - drownings go up. That just proves the causal link between swimming and drowning.
Another idea would be to see if this is a special case for this town, or a general case for all seaside town in the UK, Europe, Worldwide...
Or you could just accept that you cannot prove causality, but you have a credible explanation for causality, which is enough for a working hypothesis, but one must be open to evidence countering that explanation.
Exactly the same with Social Media and Crime with Racial Aggravation. One does not necessarily cause the other, and the only way to PROVE that one way or the other is to manipulate the Social Media feeds and observe the outcome. Now, as if ANY company with any shred of socially responsibility would undertake such an unethical experiment...
I think you missed it. There were key words, like the N* word, that had to be used in conjunction with some other defined negative word list (e.g. f*ing N*s) in order to count as a certain hit. They recognised the bi-partisan nature of some language. Machines, you see, are still f*ing stupid. Oooh! I'm being all "AI-ist" now.
My statistics lecturer (I went to a university in a seaside town) used actual data to draw a lovely graph of ice cream sales against drownings. Did loads of statistics on the data to show a very highly significant correlation, but there was obviously no causal relationship. No amount of statistics using just those sets of data would elucidate a causal relationship of course, and that was their point.
There's a correlation between absolute number of racist Tweets and absolute number of reported hate crimes. I wonder if there's also a correlation with population size? You know, places that have more people tend to generate more Twitter traffic than places with fewer people, and places with more people tend to have more crime reported. Surprisingly today we learn that there are 8,000 more theft crimes per year on the London tube network than in cities that don't have a London Underground.
I think we take it as read that scientists do take account of these confounding factors, but you can't make these assumptions. You have to state if the measures you are using are per capita or not; it's only a few extra characters.
--EDIT--
Actually, the paper's contents are much more interesting than the summary reported. Not 100% convinced by their methods, as their algorithm was very much tuned towards "white-originating" racist language than racism in general, and they did look at the racial demographics of cities. Most interesting was the pinpointing of particular "mouth-piece" racists.
I thought it wasn't so much the saving money as the being quicker to market a jet that competed in an expanding new marketplace for more efficient, quieter, cheaper to run, mid-sized carriers, to replace a fleet operating out of provincial terminals which were mostly still operating with fixed height embarkation steps rather than the full-range height adjustable jet bridges of larger hub terminals. They had shorter landing gear struts in order to get the plane to sit lower down, which limited the range of engines their airframe could carry, and had previously adjusted the engine shape, squashing the bottom flat to make it fit. The engines they needed to compete with other manufacturer's planes were bigger and rounder, too big and round to actually fit safely on the plane where they were supposed to. To go into a full development cycle for a new airframe able to lift these bigger, rounder engines clear of the ground whilst still keeping the door heights the same would have taken many years and billions of dollars. By mounting the engines in a different place on the wing, they could make it work with an existing airframe for which existing terminal infrastructure was present. But by doing that, they f***ed up the handling, which they tried fixing in software.
Methinks it would have been cheaper to just supply every airport that needed them with a new set of boarding stairs/lifts.
If you like. I was hoping for a Dr Who reference.