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Hozzáadva: 2007/01/21;
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vélemények aktualizálva:2016/05/12


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Hozzáadva: 2016/05/12

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Hozzáadva: 2014/03/05

Thanks for the reply. There's no conversion thgouh. Suppose we have the picture of a patient. Dr A rates them 4, Dr B rates them 5, Dr C rates them 3 and Dr D rates them 5. How can you use these four ratings to get some kind of measure of attractiveness? You could just sum them up. That would give you a measure of attractiveness. The advantage of taking the average and dividing by 4 is that it gives the numbers some sort of meaning on the original 5 point scale. A score of 4.5 is in the "more attractive" region of the scale while a score of 1.5 is in the "less attractive" region. It's not really continuous data, more like a squeezed 16 point scale (20 points being the highest possible score from the sum of the 4 Drs and 4 being the lowest).You'd end up with a set of data of the form Patient A-3.25, B-2.5, C-4.75, D-1.25, E-4.00 etc etc. Next you want to bin them somehow. This would be no different to binning a data set like weights. It would be legitimate to group people with weights over X as heavy, under Y as light and between X and Y as average. Similarly you can do that here to say under 2.5 is less attractive, 2.5-3.5 is average attractiveness and 3.5 and above is attractive. You probably could bin them in such a way to skew results and, if there binning was unusual (5-4 is attractive, 4-1.5 is average and 1.5 and below is unattractive) then that might suggest cheating the statistics. But their binning is such that there are 6 possible values in the attractive bracket (5.0, 4.75, 4.5, 4.25, 4.0 and 3.75), 5 in the average (3.5, 3.25, 3.0, 2.75 and 2.5) and 6 in the unattractive bracket (2.25, 2.0, 1.75, 1.5, 1.25 and 1.0). Those bins are all equally sized (along the attractiveness spectrum) and they correspond to what they were measuring (>3.5 means more scores of 4's and 5's,

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Hozzáadva: 2012/11/01

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