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Philip Howard
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At Sainsburys (UK), milk is labelled by its fat content; 4%, 2%, 1% and 0.1%. Since the alternative is 'full-fat', 'semi-skimmed' and 'skimmed', I'm much happier with the fat percentages as labels. The fact that milk has sugar (lactose) in as well as fat shouldn't really come as a surprise. Lobby your government for mandatory traffic light food labelling. It makes all this stuff straightforward for the consumer.
I don't think the charts given here are much improvement either. The assertion is that access to elite schools has not improved, so let us examine that, rather than deciding to lob line charts of one kind or another at the screen. We need to contrast earlier access with later access, show any common trends or outliers, and give some idea of how access and its change relate to exclusiveness. So make one axis the eliteness of the university (e.g. rank from league tables). Next we need a measure of access; since access per year varies, let's show the access as a delta to the overall access for each year. But we are trying to show both level and change, so how about a slopegraph as Phillip suggested for each from 2005 to 2011, but I suggest also indicating whether the movement is significant; LSE's access varies wildly and a simple slope would not do it justice. Perhaps a fit line through the points, with some shading indicating the bounds of the points. Alternatively, get hold of the ranking data for each year, and plot rank vs access as a path for each institution, picking out Oxford, Cambridge and any outliers, and using tapering or arrows to indicate the motion over time. The point is to pick the question to ask, and make sure that at a glance you can answer it. At a glance, the new chart above just tells me that there are more and less accessible universities; the ranking puts absolute accessibility uppermost, which has not changed so significantly at any university to obscure a trend down and to the right, which is just the ranking. In 5 seconds, look at the chart and tell me whether the most elite universities have improved access. A clue: their ranking is not even present on the graph.
I think in this instance, Jeff, you're wrong. A mayor who knew how to code would be a great improvement. Perhaps he doesn't need to learn how to code, but ideally he would know about data, standards, algorithms, security, privacy... a lot of the job of a mayor is dealing with bureacracy; if that mayor could tell when there was a technical solution to a problem that avoided the bureaucratic one, maybe he could spend less on the bureaucracy. Your wider point that not everyone needs to learn to code is true, with the same caveats; if you don't know when code can solve a problem, how will you know when code can solve a problem? I've helped many people in the past with macros that saved them hours of repetitive work - they just didn't know it could be done. As others have pointed out, most people don't use much of their school education, but it serves the important purpose of telling you what kind of thing is out there, should you need to know it. Learning history tells you something of the politics of a situation, and this is a similar arena needing context. TLDR: maybe not coding as such, but everyone would do well to gain awareness of code and its capacity to solve problems at scale. Frankly the simplest way to learn that is to learn to code a bit.
Toggle Commented May 15, 2012 on Please Don't Learn to Code at Coding Horror
Shannon's sampling theorem tells us that at a given sampling frequency f, the sample can exactly represent the signal up to the Nyquist frequency, which is f/2. The problem is not that the screen is too low resolution, if you can't see the individual pixels. The problem is that the signal is aliased, which means that it contains components with a frequency (detail level) too high for the screen. The correct answer is not to smooth the image after you have created it; that will lower the Nyquist frequency of the image, but not improve the original signal. The correct answer is to reduce the frequency of the signal. This means doing MPAA to get the higher-res sampling (and capture the original signal better) then do Guassian convolution over the image, before finally sampling that for the screen. All you have with FXAA is vaseline on the screen.
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Dec 23, 2011